Good afternoon everyone. I think we have a couple folks settling in but we're gonna get started because I know everyone's very anxious and the room is wonderfully full almost. Well everyone welcome to Cooper Hewitt's Smithsonian Design Museum. My name is Kim Robledo-Diga. I am the Director of Learning and Audience Engagement here at Cooper Hewitt's and as you've seen probably from the slide deck that was previous to this slide you are part of a program. This wonderful program is part of our National Design Week so hopefully some of you've been taking advantage of our other programs this past week and we have free admission through Sunday so please do continue to come back. So I'm happy to introduce Keith Talian who is a New York City historian, writer, researcher, and tour guide. His Instagram account at Keith York City seeks to unpack the city's history and help readers better understand and appreciate its development. Many of us have experienced New York City through the history and its history of the built environment through Keith's Instagram account which currently has over 45,000 followers, hopefully another 80 so plus more after today if they aren't following already, and during the uncertain days of the pandemic we could you know roam around New York City and learn about its buildings and peoples through Keith's engaging and informative content so he kept us connected with the city when we're all locked down. Keith and his work have been featured in The New Yorker, The Times of London, and The Daily Beast, Surface Magazine, Condé Nast, Traveller, and El Decor. He has been a guest lecturer at Cooper Hewitt, Atlas Obscura, Parsons, the New School of Design, and Robert A.M. and M. Stern Architects. In 2020 he walked every street in Manhattan and he resides in Harlem. A note that this week is the last week for the Sarah and Eleanor Hewitt Designing a Modern Museum exhibition on the second floor. It closes at the end of this Sunday and the exhibit charts the history of this museum and it's remarkable remarkable women who founded it so please take advantage today because it closes at the end of Sunday if you haven't seen it already. Thank you to Adobe, IBM, Metta, the Hirsch Family Foundation, and his generous supporters including Cooper Hewitt's Board of Trustees for making this program possible. I also like to thank, before I pass it off to Keith, my amazing team that I'm lucky to be a part of. We have two Alexis, Alexa Griffith and Alexa Cummins, Sheamus, Angela, Kirsten, Miguel, Robin, Daniela, and Emily who either hosted you coming in, checked you in, is currently videotaping this or managing the lighting, lots of behind-the-scenes and some will be participating and helping you during the walking tour this afternoon for those who you are attending that. So I am going to stop speaking now and pass you off to the person you're here to see. So welcome Keith. So my word's not going to fall. Let's see what happens. Hi everybody. Thank you so much for coming out to listen to me yammer about history, the way I love to so much today on this beautiful Friday. Today's lecture is going to be a sensibly talking about the neighborhood in which we're all sitting and standing right now, Carnegie Hill. I was talking before my lecture today that I'm going to be struggling today because I'm trying to train myself to say Carnegie, the way that Andrew Carnegie would have said it, which is Carnegie, but something about saying Carnegie Hill doesn't feel right in my mouth. So we'll see how I do with that today. Today's lecture will be split up roughly into four parts. One, infrastructure. Two, the Gilded Age. Three, Yorkville, and four, Carnegie Hill will unpack essentially how the neighborhood where the Carnegie mansion now stands came to be. Part one, infrastructure. As of the early 19th century, New York City was an established port town on the American Eastern seaboard, one of several large and prosperous towns like Boston, Philadelphia, Charleston, even New Orleans, all towns that were vying for economic and commercial primacy in the relatively young new nation of the United States. Now at the time, the United States, the original 13 ish colonies were rapidly expanding into what's now what we would now call the Midwest, what we're then called the Northwestern Territories, as well as the newly acquired Louisiana Purchase Territories. Pretty much about the central third of what's now the United States had recently been acquired and was rapidly being divided up into territories and new states. So there was a lot of raw commercial product being produced in these Northwestern colonies and territories, and also a large and growing market for goods produced or imported on the Eastern seaboard to be sold to people moving out there to the west of the Appalachian Mountains. And the issue was that in an era before any sort of rapid transportation, obviously before highways, but even before railroads broke into the American interior, there were really three main ways in which commerce could get in or out of what's now the Midwest. Those are represented by the three lines on the map. Behind me right now, one of those, let's say you lived in Wisconsin, you needed to get lumber to market. You could float that lumber by barge down the Mississippi River out New Orleans through the Gulf of Mexico around the tip of Florida and then finally up to the Eastern seaboard or across the Atlantic to Europe. This process took weeks and was very expensive and completely reliant upon the ability to reserve a space on a barge and to get your product onto it. The second option is represented by the short line in the middle there. This is an overland option, whereas you could put your goods onto a wagon that would then be hauled over rutted dirt roads over the Appalachian Mountains and then down the other side onto the Eastern seaboard to then be brought to port and either sold or sailed over to markets in Europe. Just like the Mississippi River option, this took many weeks and cost a lot of money and was also rather risky. If the wagon broke down, you could potentially lose whatever goods you had on it. But as difficult as those two options were, the third option was arguably the worst of the three and that's the line that goes up around through the St. Lawrence River in what was then British held Canada. Remember that we're talking the 1820s, we had just barely finished fighting the War of 1812 against the British primarily via Canada. So sending the economic lifeblood of our growing country and economy through the center of a British held territory didn't seem like the most ideal of methods and even then even if it wasn't so bad geopolitically, it took just about as long if not longer to sail your goods up through the St. Lawrence around Gaspe Point and Nova Scotia and then down to the Eastern seaboard or to Europe as it did to send it down the Mississippi or over the Appalachian. So all that's my long winded way of saying that there were no good options to get goods in or out of the territories and states on the other side of the Appalachian Mountains and New York State set about to change that. The result of that was the opening of the Erie Canal in 1825. What the Erie Canal did was literally cut a waterway across the width of New York State connecting Lake Erie at Buffalo to the Hudson River near Albany. Pretty much overnight when this opened in 1825 it revolutionized not just New York's economy but the entire country's economy. Now goods rather than going down the Mississippi over the Appalachians or over the St. Lawrence and around Nova Scotia goods could just sail via the Great Lakes through Buffalo across the width of New York and then down the Hudson River and out New York Harbor either to markets elsewhere on the Eastern seaboard as I've been saying markets in Europe. Something like 80 to 90% of all goods that used to have to pick their poison so to speak the Mississippi or the Appalachians were now redirected directly through New York Harbor which answers the question that I get a lot when I do walking tours of why is New York so why did New York become so much larger and more important to the nation than any other port town. There were lots of other good ports. There were lots of other cities about the size of New York at the end of the American Revolution. How did New York become so singularly successful and arguably I would argue that you can point directly to the Erie Canal is the reason for that. Now with the opening of the Erie Canal in 1825 the city's population and economy grew by leaps and bounds. You can see this drawing this drawing was actually made around 1850. This is looking at Lower Manhattan the green patch on the left is Battery Park. If you look closely you'll start to recognize some church steeples like Trinity Church, St. Paul's Chapel. You can even find City Hall on this map. But what the reason I cropped this map down to just this area of looking at Lower Manhattan is I want you to look at the waterfront down at the bottom of the image. Look at how many ships the artist has drawn here. Now obviously there's some artistic license involved here but the point of this was to impress upon viewers just how busy and prosperous the New York City Harbor was in the decades following the opening of the Erie Canal. There are so many ships here you really can't pick one out from the others. This is meant to celebrate New York's economic prosperity but with that prosperity came real urban issues things that we still to a certain extent struggle with today but namely overcrowding and disease. This is a clipping from I think this is the New York Herald it might be the Tribune one of the two before they became the Herald Tribune and then went out of business altogether but this is a list of business announcements from 1822 so just before the Erie Canal opened so this was already an issue before the canal exacerbated it but these are all listings from businesses in New York City announcing that they were moving out mostly to Greenwich Village to escape the seasonal sickness. Most of these just say removed for the present from there I'm looking at one Thomas Dixon and Co on the left side the fourth article down Thomas Dixon and Co have removed for the present from 77 Pine Street so down in what's now the financial district to the corner of Hammond and Greenwich streets and that's what all of these ads were and this is just a snapshot of an entire page filled with ads like this and some of them more specifically if you look two down from the Thomas Dixon ad that I just talked about the Benjamin McCready ad it more explicitly says Benjamin McCready has removed parentheses during the sickness to Brooklyn near Pierpont Distillery fifth house from the military garden in Jirolemans Lane so this the unhealthiness of this rapidly growing city threatened to upend all the economic success that came with the opening of the Erie Canal and so in response to that the same way that New York leaders had opened the Erie Canal to harness that economy that economic success they set about to cure the problem of health in the city by building the Croton water system which was completed first in 1842 what the Croton the original Croton water system was and we still generally rely on the system just a wholly new system of reservoirs and aqueducts today but what it did was dam up the Croton River in West Chester County which is on the left side of the map on the screen and then run the freshwater from the resulting lake via system of like 40 miles of aqueducts down through what's now the Bronx across the Harlem River into what's now Washington Heights Harlem the Upper West Side and finally to a collecting reservoir in the middle of what's now Central Park Central Park wouldn't exist for another decade and a half after this was open but then from that first reservoir the water was piped under Fifth Avenue to a distributing reservoir at what's now the New York Public Library that was in a nutshell the city's first comprehensive water system giving the city and its rapidly growing population clean drinking water so that we didn't have annual cycles of cholera typhoid and yellow fever washing through the population and upending the the city's ability to continue growing but what this did was encourage the city to continue growing north this is an image from 1853 the year that New York hosted the United States First World's Fair you can see the Crystal Palace that used to stand where Bryant Park is today in the forefront on the right of the screen to the left of that Crystal Palace which was built by the same architect who did the Crystal Palace in 1851 in London we brought him over so that we could try to copy London as closely as possible but you'll see a raised giant swimming pool that is the distributing reservoir of the Croton system and just beyond that you can see what's now Murray Hill and the theater district Murray Hill on the left the theater district on the right this was pretty much the extent of the city's populated area as of the 1850s when the World's Fair was held in what's now Bryant Park they were actually interestingly reports in the newspapers in 1853 of tourists visiting New York to attend the World's Fair and being unable to get up there because the street cars ended about five blocks south of it so people would come here they'd enter in New York City which was then lower Manhattan ride a street car or a carriage all the way to the edge of town and still have to walk another quarter mile through the dust and and fields to get to the World's Fair but that aside New York was rapidly growing and succeeding and by the time the population grew up into what's now Murray Hill and approached 42nd Street and the Gilded Age was beginning to dawn now I do a Gilded Age walking tour pretty often and I always start long before the Gilded Age actually began historically the Gilded Age is dictated as being somewhere between 1870 and 1910 those are the somewhat hard boundaries of what we consider the Gilded Age but really the reason I did part one on infrastructure is because it was the Erie Canal and the Croton water system that allowed the city to grow and prosper to the point that we can have Gilding on our otherwise Manic City because that is an important distinction here to make is that we had a Gilded Age not a Golden Age where if you compare the two Gilding is a very thin layer of gold over something less valuable beneath that's what we had we had a very small wealthy population over an otherwise teeming and chaotic city now going back this is the map that I had zoomed in on earlier but panned out to show the entire thing and you can see how concentrated New York City's population was on the lower end of Manhattan in fact as an artistic interpretation of the city at the time they have blown up lower Manhattan to make it look even geographically larger than it actually was you can see just across the river in the background the little cluster of buildings that's now roughly Jersey City and then the bare land up the Palisades on the west side and you can just see a little inkling of Governor's Island at the bottom and Brooklyn on the right but the focal point of the image of Manhattan itself I've drawn a line on the map depicting the location of 40th Street and you can see that everything north of 40th Street is just kind of faded out to nothingness because there was really nothing up there if we zoom in on the area north of 40th Street I've left the line and placed at 40th Street here and if you look closely the most if I don't know how clearly you can see this from all the way back in the audience but if you look closely at the map here you can see a little train chugging down the middle right part of the island that is what's now Metro North so that's Park Avenue and then if you look immediately to the left of the train right up against the black line I've drawn on 40th Street you'll see a little castle type building that is the distributing reservoir that I showed a couple slides ago in what's now in what's now Bryant Park where the New York Public Libraries now stand so that should help place you here and but more importantly show you how little thought really was given to drawing the upper part of Manhattan and when I say upper I mean north of 40th Street we're not talking all the way up here where we are 90th and 91st streets that's not even on the map it was so rural that pretty much everything north of about 86th Street just vanishes off into the ether at the top of the map here if you look closely at the map find the train again on the map and look just above it you'll see a little castle building that is the armory in Central Park where the zoo is today and just above that you'll see another swimming pool that is the other Croton reservoir so the the collecting reservoir so that was the water's first stop in Manhattan that was demolished in the 1920s to make the great lawn in Central Park so again just to help place you on the map here so what was going on north of 40th Street that was so unimportant first you have to remember that Central Park wasn't even approved as a concept until the early 1850s and it didn't really begin opening to the public in phases until the early mid-1960s and wasn't completed until the early 1870s so when the Erie Canal was completed we're talking 30 to 40 years before Central Park was even completed so there really was no pull to the north for the city other than a general desire by the city's wealthy population to flee from the increasing density and commercialization of the city as it existed one of the greatest themes that you'll find when you research New York's growth particularly in the 19th century is that wealthy people constantly were pushed and pulled out of the city pushed by the increasing industrialization of the city you didn't want to live next to a factory or a hotel or a brothel but also pulled because the land on which their houses stood in older neighborhoods like let's say a wealthy family lived for generations on Battery Park with the opening of the Erie Canal and the increased commercialization of the city that land where their house stood was now much more valuable as a redevelopment site for a warehouse or a hotel or a brothel and so with that profit in mind families would very quickly sell their houses in the old neighborhood that would be redeveloped and the family would then reestablish themselves in a new neighborhood on the edge of town away from the factory's hotels and brothels this happened again and again about every 20 years about every generation wealthy New Yorkers would decamp the overcrowded city to the edge of town they would then be followed by commerce who wanted their business the business would then be followed by industry which wanted to provide goods to the businesses and then the industry would be followed by tenement and poor immigrant districts to provide laborers to work in those factories and suddenly within 10 or 20 years the people who had moved out to the countryside found themselves surrounded by the same city they had been trying to escape and so with that cyclical action moving north ever northward up the island Manhattan eventually filled up which is how not to give any spoilers but that's eventually how we end up with the area where we're sitting filled up but how specifically Dekarney, Ghee Hill become what it is today so this the image I have open the screen right now is number four West 54th Street it's an interesting house unto itself it was later purchased by John D. Rockefeller and then was demolished for an expansion of MoMA but it was one of the first Brownstone true Brownstone mansions built north of 42nd Street it stood on 54th Street which was in the 1860s still a bit of a hinterland you can see just behind the house there are literal wooden shacks and open fields behind it the streets have been laid out on the left that street you can see running diagonally on the left side of the image is Fifth Avenue this was about as populated as the area between what will become Central Park and the reservoir of 42nd Street was for most of the area during the Civil War this is one of my favorite photos depicting that area so this is around 1871 looking northwest from 55th Street and Madison Avenue the prominent gravel road there is Madison Avenue and you can see there's a church under construction on the right and a cluster of houses in the background most prominently if you look closely at that cluster of houses you'll see one of them with a very high mansor groove is white whereas the rest are all brown that white one is the marble row of Mary Mason Jones who was what's the word I'm looking for she was placed in history by her distant cousin Edith Wharton in the Age of Innocence she's Mrs. Manson Mingott so Mary Mason Jones I just like to point out that house because she built her house at 57th Street where the Louis Vuitton Store is now in 1869 which if you remember 1869 I mean that's this is roughly what the rest of the neighborhood looked like a house here or there but otherwise dirt fields goat farms and dusty gravel roads and Mary Mason Jones had inherited land up in that area in the 1850s or 60s and decided in 1869 rather than to resell the land or lease it out to someone else that she would actually build her own house on that plot of land so in 1869 long before anyone else thought to do so she moved up to 57th Street and as Edith Wharton would later say would sit in her parlor window looking south waiting for society to catch up to her which is also why there's a somewhat apocryphal tie between Mary Mason Jones and her family and the phrase keeping up with the Joneses because people were trying to keep up with her who was ahead of the time but all that is to say that Mary Mason Jones moved up there just as Central Park was beginning to open up it was Central Park was as I said first approved in the 1850s began opening to the public in phases in the 1860s these two maps here depict the land that would become Central Park as it existed originally and then the plan that it would become after being designed by Frederick Law Olmsted and Calvert Vaux at the bottom and the top map interestingly you can see the reservoir that I pointed out earlier on the map at the center of the park what's now the great lawn and just above that on the map you can see a little smattering of dots those are the buildings of Seneca Village so that's the mostly the black majority community that was evicted to build Central Park as Central Park opened it did make the land north of 42nd Street more attractive to people beyond just Mary Mason Jones and that one brownstone on 54th Street but the question was as wealthy people began to be commercialized out of Murray Hill which was for most of the Gilded Age the premier neighborhood for people it was anchored by Mrs. Aster Carolyn Skirmahorn Aster who lived at 34th Street the question was that inevitably Murray Hill would convert to commercialism and industrialization and where would the wealthy population go next would they push north of 42nd Street into the no man's land between the reservoir and the park or would they leap all the way over that no man's land ahead of Mary Mason Jones to live on this newly established park would this be enough of a draw to make people skip a mile of the city and move all the way north oh I forgot I have this picture in here so this is another picture that I love this is where the Pulitzer Fountain is today in front of the plaza you can see the trees in the background that is Central Park so this is the southwest corner of 59th and 5th looking up into what would become the park so this is what Mary Mason Jones moved into essentially and the question of what would happen to the area north of 42nd Street was mostly answered by the Vanderbilt family the Vanderbilt's made their initial fortune in fairies the Vanderbilt's were an old Dutch family farming and running a small estate on Staten Island and in the Raritan River Valley across the kill in New Jersey but Cornelius Vanderbilt known to history as the Commodore took his father's fairy business his father would run one boat between Manhattan and Staten Island and other points around New York Harbor but young Cornelius took his father's boat and business and expanded it radically buying more boats hiring more pilots and running more and more fairy lines around New York Harbor Long Island Sound the Hudson River and along the eastern seaboard of the U.S. Now that's not how we tend to think of the Vanderbilt's we think of them as a railroad family and the reason for that is that by the 1860s Cornelius the Commodore recognizing that fairy travel was not the way of the future began to divest himself of his very fortune and reinvest that money in railroad his three chief acquisitions in the 1860s were the New York and Harlem Railroad what's now Metro North on 4th Avenue the New York and Hudson Railroad which is now Amtrak along the Hudson River in Manhattan as well as the New York Central Railroad which runs it's now Amtrak between Albany and Buffalo and points beyond out to Chicago those three railroads combined he then named collectively the New York Central Railroad and with the acquisition of all those lines the consolidation of his whole rail system he built a new Grand Central Depot depicted here at 42nd Street and 4th Avenue or Park Avenue this was meant to establish the primacy of the New York Central Railroad in New York but what it served to do more tangentially was that it established a new center for a new potential center for society on the north side of 42nd Street because immediately with the opening of this train terminal everybody traveling into New York from points beyond like Albany or Boston were now being disgorged on all the way up on 42nd Street in that no man's land that people had been speculating about this terminal the Depot opened in 1871 roughly on the site that the current terminal sits which was completed in 1913 around the Depot though grew very rapidly a collection of hotels to serve those tourists pouring into town which became an attraction in and of themselves to New Yorkers wealthy New Yorkers high society New Yorkers that previously would have gone down to someplace like Madison Square to eat in the restaurant or go to balls at hotels down there now found a new hotel social tourism travel center opening up around 42nd Street now carrying that Vanderbilt family influence forward Cornelius the Commodore died in 1877 and his estate worth somewhere around 150-ish million dollars in 1877 passed whole to his son almost whole to his son William Henry Vanderbilt otherwise known as Billy Billy had eight children and Billy his wife and six of their children immediately took their inheritance and moved north of 42nd Street where they could where they were able to in that no man's land again between the reservoir and the park they were able to get lots of land big enough to build houses commensurate with their new found wealth the Vanderbilt family had otherwise been clustered down around 4th Avenue on the east side of Murray Hill but now flush with all of their patriarch's inheritance money they wanted to build something that said that the Vanderbilt had truly arrived in society and so that open land they 5th Avenue by this point had been cemented as the city's chief wealthy address and the only stretch of 5th Avenue that was still widely available for building but still close enough to the city to partake in all the social comings and goings that were happening in Murray Hill was that no man's land between the reservoir at 42nd Street and Central Park at 59th Street and so Billy and like I said six of his adult children moved into a row of mansions on the west side of 5th Avenue between 51st Street and 58th Street they built seven mansions I did mention that Billy Billy who lived in the frontmost mansion here closest to the camera this is 51st and 5th so where his mansion stood is now Victoria's secret I don't like saying it any more than you like hearing it lost my train oh so he had eight children just to close that out six of the children on this row of mansions and what was known as Vanderbilt Row or if you didn't like the Vanderbilt to Vanderbilt Alley the other two children that didn't move into this row was his third son Frederick who's more famous for building Rough Point in Newport and the Newport mansion at Hyde Park he and his wife moved into Billy's old mansion at 40th and 5th where the Stavros-Niarchos branch at the NYPL is today not the same building it was torn down and replaced by a department store that's now a library it's just it's all very hard to keep up with but that's where he lived and then the youngest son George Washington Vanderbilt the second was too young to have his own house and by the time he came of age didn't want anything to do with Fifth Avenue Society so instead he took his inheritance and moved down to the foothills of the Appalachian Mountains in North Carolina and built built more estate down there so that's when we think of the Vanderbilt and Gilded Age mansions and we see pictures like this and we immediately know what time period we're talking about these are the Vanderbilt's we're talking about the son and grandchildren of the Commodore who established the family's fortune this is the largest of all the Vanderbilt mansions this is looking southwest from 59th and 5th this mansion was later replaced by Bergdorf Goodman but this was the house of Billy's eldest son Cornelius Vanderbilt the second really just to show you what became of that No Man's Land stretch so where just 20 years prior Mary Mason Jones was living alone in her marble house you now can see a non an unbroken line of very fine Chateau-esque mansions and church steeples running from 58th street all the way down contiguously into Murray Hill this is where the Gilded Age occurred generally speaking old money families living south of 42nd street in Murray Hill new money families spearheaded by the Vanderbilt's living north of 42nd street now moving on to part three what was going on up here while all of that was happening down below 59th street and that was the town of Yorkville Yorkville existed roughly centered on what's now 86th street between second around second third and fourth avenues or park at what would later become Park Avenue people began moving up there starting in the 1830s with the arrival of the New York and Harlem Railroad one of the lines that would eventually be purchased by the Vanderbilt's the New York and Harlem ran down the center of Fourth Avenue and had a station at 86th street in what was then the middle of nowhere but with that station opening some people began to move up to the countryside to establish a little village unto itself around that station and that village was later christened Yorkville now interestingly just as an aside here not to get too off track but York Avenue was actually not named after Yorkville or New York it was named after a World War I soldier whose last name was York I grew up thinking that Yorkville was named after York Avenue but that is not the case maybe you all knew that so it was interesting to me but Yorkville was largely populated by in addition to those original settlers who moved up out of the city to the rural town of Yorkville halfway between New York and Harlem its population boomed in the 1830s not only because of the opening of the train but because workers moved up there to be in close proximity to the Croton Reservoir which was being built in the 1830s the smaller rectangular reservoir in the middle of the map of Central Park here that was the reservoir being built as part of that original water system that I talked about before and mostly German and Irish workers moved up to Yorkville to work on building the reservoir and aqueduct system and then many of them stayed and so that community of laborers who moved out to the countryside coalesced as the town of Yorkville but you'll notice on this map that the population center is far east it's not on Central Park at all and that's because even by the time Yorkville began to grow as a community developers and speculators recognized that Fifth Avenue land on Fifth Avenue was valuable and so the land on Fifth Avenue fronting this new park was held off and put up for sale at a much higher price than land off Fifth Avenue so even if people living in Yorkville had wanted to move on Fifth Avenue the land was generally kept out of fiscal reach of most of the people living there at the time so Fifth Avenue remained a largely undeveloped thoroughfare this far up on the island this is a view looking out over the heart of Yorkville in the 1870s you can see rows and rows of brownstone houses not terribly large and luxurious but these are the kind of houses that the laborers who moved up here the German and Irish immigrants who moved up here to work on the reservoir and then later to work on the elevated trains and the breweries that were attracted to the area these are the types of houses they would have lived in you can see the rows of modern brownstones in the foreground but just behind them to the left you can see little wooden houses many of which are below street grade because as the streets were laid out they had to be raised to be flat and so a lot of those original wooden houses built up here by the first wave of Yorkville residents were then stuck under street level if you can't talk from this image just look beyond the rows of brownstone houses here you'll see an elevated train line that is 3rd Avenue and then behind that in the distance you'll see another train line off in the distance that's 2nd Avenue the 2nd and 3rd Avenue Elves which would remain in place until the 1930s and 40s this image is looking south from the same location so these pictures were taken from the roof of the home of a German brewery owner named George Aret and he had a brownstone mansion at 94th and Park so that's where all these pictures were taken this is looking south again showing rows of brownstones that were being built in the 1870s to house many of the New Yorkers some of them solidly middle class moving up here to live in the countryside if you're familiar at all with the area if you know that there are two wooden houses on 92nd Street east of Park Avenue those are the two wooden houses on the left with the shutters the white houses there that are next to each other those still stand today and then finally this is looking north from that same house this is Park Avenue made of dirt where the train the Fourth Avenue train emerged from the tunnel running under Fourth Avenue which was rebranded Park Avenue to euphemize the fact that trains ran down the middle of it but you can see the large berm on the left side of the image and beyond that is Central Park so this is roughly what what's now Carnegie Hill looked like in the 1870s and 1880s while the Gilded Age and all of its splendor was occurring down in Murray Hill and Vanderbilt Row by the 1890s some people some old money families namely Mrs. Aster Carolyn Scurmerhorn Aster began to creep north of 59th Street but they generally did so one block at a time just about Carolyn specifically moved up to 65th Street where the Temple Emmanuel stands today that's where her house was in 1895-1896 when she completed work on a hotel on the site of her former house 34th Street it's a whole story she had a feud with her nephew and his wife over who got the title of Mrs. Aster and in spite her nephew tore down his inherited house at 33rd Street and 5th and put up a hotel that he called the Waldorf she then not wanting to live next to a 13 story hotel tore down her own house built this and moved up to 65th Street and in place of her house built an even larger hotel to compete with the Waldorf which she called the Astoria so the Waldorf and the Astoria stood there competing with each other until Carolyn died in 1908 her son John Jacob IV died on the Titanic in 1912 and her half of the estate passed to his son Vincent the other side of the family the estate passed down to her nephew's son Waldorf and Waldorf and Vincent united the hotel as the Waldorf Astoria and then in the 1920s sold it to a group of businessmen who tore down the hotel to build the Empire State Building that was a tangent I didn't need to go on but I did but this is roughly what lower Central Park Fifth Avenue looked like in the 1890s when Mrs. Aster moved up to 65th Street you can see a steady row of mansions but just north of this north of 72nd Street or so the mansions would have petered out and become just block after block of open dirt fields waiting for someone to buy them there were actually news complaints I was reading about while preparing for this lecture people complaining that all the unsold lots were surrounded by wooden fences that were then covered with billboards making a garish spectacle of every color and crass reference you can imagine now up in Yorkville this is what the area looked like at the same time that previous image was taken so 65th Street 94th Street this is the difference the only mansion you see in this image is that that large house on the left that is the mansion of Jacob Rupert if you're familiar with the Rupert towers over on was that 3rd Avenue 2nd 3rd Avenue those towers were built on the location of his brewery so as a wealthy brewer just like George Arrett from whose house this picture is taken Jacob Rupert built a house up on 5th Avenue but he was as you can see very much alone with his house overlooking his house stood at the southeast corner of 93rd and 5th that's what you're looking at with what's now the Jackie O Reservoir just beyond now everything changed at the end of the 19th century when this area this western relatively undeveloped stretch of Yorkville became Carnegie Hill Andrew Carnegie was born in Scotland I believe in 1838 I have the dates on a later slide so we'll see if I'm right or wrong but he was born in Scotland immigrated to the U.S. to specifically Allegheny County, Pennsylvania when he was about 10 years old with his parents there he got into the rail industry and then segued his way into the steel industry as a young man got very wealthy off of this but did not marry until late in life he was very devoted to his mother and she lived until late 1886 and so Andrew Carnegie didn't marry until his mother passed away so he married the woman you see here Louise Whitfield in early 1887 on their marriage Andrew did have her sign of prenuptial agreement which provided her believe it was $20,000 a year in exchange for her not if they ever were to split up she would not get access to any of his fortune so she got $20,000 a year in 1887 which today is about $650,000 a year as an allowance and he also gave her the deed to this house which he purchased for them which stood at 5 West 51st Street where the Women's Republican Club House is today across from Rockefeller Center that's where his house was just behind Billy Vanderbilt's house that you can just see peeking into the camera from the right here with the Corinthian columns surrounding the window so this is where Carnegie and his wife lived after their wedding in 1887 Carnegie by this point in 1887 when he got married he was already 52 years old his wife Louise was 22 years his junior and so having a relatively mature but wildly wealthy and famous man married in 1887 made all the social papers as you can see a clipping of their wedding announcement here on the left that the wedding took place at her mother's house but anyway more importantly the couple didn't have children for a decade into their marriage and when they finally did have a child having an heiress to the Carnegie fortune was also considered newsworthy the daughter Margaret was named after Andrew's mother who had passed away prior to his marriage to Louise Margaret was born in 1897 you can see the article here on the right Mr. Carnegie's expectations talking about the expecting of the first Carnegie child now with the daughter born and with Andrew recognizing that his career and time on earth may be coming to a close in the not too distant future he decided to devote himself more to domestic life and so very secretly he began buying up plots of land far up on northern Fifth Avenue between 90th and 92nd Street he amassed a collection of it was something like 20 buildable lots on Fifth Avenue and the side streets around it he would not publicly admit to buying the land and so you can see from these articles that I pulled on the one on the left is from late 1898 where the real estate pages in the New York Times are speculating that Andrew Carnegie is the buyer of all these lots up at 90th Street but the right article from early 1899 four months after the previous article says aside from the amount involved the purchase of this property by Mr. Carnegie was of special importance in that the limit of the fine residence section of Fifth Avenue was carried about a half a mile further north and the effect of the transaction has been clearly shown in the remarkably active dealing of the last two months in lots between 80th and 90th Streets so essentially the gap of 10 blocks between the established area down around Mrs. Aster's house at 65th Street and this formerly isolated German Brewer District up here north of 86th Street began to be accepted as part of the inevitable northward march of the guilt age society with the arrival of Mr. Carnegie up here in 1898-1899 now in July of 1899 the first etching of his planned house was released to newspapers this is from the New York Times showing the house it was built roughly like this today the major difference is that the left wing the eastern wing of the house wasn't built to a full four stories as shown in this image but what I find interesting is that Carnegie was a very for how rich he was he was a very frugal man and he ordered the architects to design for him a simple but roomy house having a large lawn was important to him you'll notice that the house even today that we're sitting in and it has a very nice large garden in the back that was important for him in his old age to have a place where he could go outside and commune with nature he actually had more than a dozen mature trees dug up in Westchester County and Connecticut hauled down to the garden here and planted in place but the press and much of society was surprised and possibly disappointed in the design of the house because they thought it far too plain for a man of Mr. Carnegie's wealth they said it looked like a large brewery keeping up with the the theme of the neighborhood up here but Carnegie wouldn't have had it any other way and so the house was completed in late 1901 early 1902 the finishing touches were being put onto it but even by then newspapers had begun to refer to this area this rise of land where the house was built it had previously been known as Prospect Hill but newspapers quickly after they found that Carnegie was the buyer of the land up here they began to refer to it as the Highlands and it didn't take long after the house was completed for developers to rebrand it as Carnegie Hill in honor of the biggest attraction up here at the time this article is from 1812 or April 12, 1903 barely a year after the house was completed and you can see a view looking north with the Carnegie House and the distance here but showing the types of houses being erected on the blocks just south of it and this district talking about the phenomenal growth of the Carnegie Hill section as more and more mansions were put up on Fifth Avenue and the surrounding blocks now this I found interesting this is in the same newspaper the same day but shows two different ads one shows the Carnegie Hill Hotel which still stands today as the I think it's called the Whales it's an apartment building on 92nd and Madison this is the first institution as far as I can tell to take the name Carnegie Hill it was built as the Carnegie Hill Hotel but I included also an ad for two houses on 89th Street on the left because if you look closely just below the address you'll see that it says in their designing construction they compare favorably with the finest houses on Carnegie Heights so they were still debating what to even call the area but it definitely had the name Carnegie in it now 10 by 1913 10 years later the area had pretty much filled up as one of the city's greatest mansion districts so you can see this article from the New York Sun declaring new and finer Fifth Avenue on Carnegie Hill and displaying anchored by the Carnegie mansion at the center of the page all the fine mansions going up around the mansion ostensibly because and only because Carnegie had moved this far north so today a hundred and 20 years later we sit inside the house that made this neighborhood what it's now known as so thank you all and thank you Mr. Carnegie yep yes I just wanted to recommend Downey Grand Central Station in Vanderbilt Hall for the next week or two is the Regional Plans Association yes really wonderful display of a hundred years of four regional plans and for New York City including the future and it builds so much on this wonderful talk of yours that I stumbled on I recommend yes yeah I saw the ads for it I haven't made my way over there yet embarrassingly but I do highly recommend that as well talks about the growth of the city and plans for growth of the city and that's at in Vanderbilt Hall in Grand Central Terminal right now so I know it's all over the map literally and figuratively in this speech so I understand their questions does anybody have any questions for me yes so after Carnegie dying his wife stayed here no it was taken what was it NYU or was it Columbia Columbia thank you Columbia used it until I believe 1973 when it was taken over by Cooper Hewitt which had previously been in the Cooper Union down in Astor Place any other questions those white small white wooden homes that are still existing on 92nd Street are they inhabited or are they inhabited yep they're still inhabited at least one of them has been expanded a bit you can if you walk by you'll see they've added some extra floors to it but otherwise it looks very much like it would have looked in 1865, 1870 which is fantastic that wooden houses have not only survived all the caprice of aesthetic choices over the over the previous century and a half but also that they haven't burned down like so much of New York did any other questions yes although in the back as the Astors and Jones and that's a good question and everybody has kind of their own story mixed into that generally speaking a lot of old landowning families had been given land by either the Dutch West India company or by the English crown over time one of the most notable examples of land speculation if that's what you want to call it was John Jacob Astor himself he came over to the U.S. in the late 18th century as to work in the fur trade but reinvested the same way that Cornelius Vanderbilt later did by reinvesting his ferry money into railroads John Jacob Astor reinvested all the money he made in the fur trade by buying up cheap land up the length of Manhattan Island recognizing very astutely that the city could only grow in one direction as it grew so he and people of his ilk would often buy up old farms and estates and sit on them knowing that the city would inevitably catch up and make the land much more valuable and so over time either Astor or his heirs as the city caught up would drive roads through their land and then divide the land up into buildable lots and sell them off one by one making a massive profit off of what had been a cheap investment 20, 30 years prior so not just John Jacob Astor I use him as one example but generally speaking it was either old families that inherited their land long before the city was anything more than little port town or land speculators who gulped the land up later as they recognized which way the city was growing any other questions cool I answered everything thank you so much for coming


Okay, and here's a quick run-through of the setup for Core ID signing code, or just entire screen, eh? Yeah. Okay, and... All right, go through setting up Core ID, the first thing we want to do is pull the repo, which we already have in this particular computer, so we won't go through that, but where's the term? Oh, you had it right there, almost all the way to the left. Do you remember where you had it installed? It's on the desktop. The Core ID stuff? Oh, the Bitcoin stuff. Well, I mean, we can do that first. We might need to pull the repo. Okay, so we're going to start by running the Bitcoin D server, and now it's running better than the other computer, yeah. And now, next we need to make sure that it has correct configurations, so in macOS X, if you navigate to the library, I think application, report, Bitcoin, it's right, yeah, and so you should be able to find this folder. We've already set this up before, but if you run that slash Bitcoin D initially, it'll just generate this folder, and you can delete all the contents and just add the Bitcoin dot com folder, which is the configurations we have listed, and right here, the documentation, like just copy over this config, if I cat this Bitcoin dot com, you see that it's the same. So it's great, it works. Next now, we want to go to the repo itself to run the code, so let's see, do you remember where you left the repo? It's in our ID hub repos, but where's that, if you list, it'll be one of the things that pops up. So now, you don't, maybe we need to like sync it, oh no, it's the wrong one, it's not there. Oh yeah, right, there's a few forks. Just to make sure we're up to date, get a pull, and now we have everything, and then we run npm install just to make sure we have all the packages nice, and we have to run nginx. Let's make sure, let's creatively spell the name of the package today. If you don't have nginx, you can install it with home group, it should be pretty simple. Right, I should have it from Friday, I think. Yeah, you should have it running, we're the command for running it for nginx, so for us, so for us, we have these config files, and so we're going to, if you cat this nginx, we're going to modify right here. So we've copied over our location, we'll copy it over how we proxied over, we're going to proxy, and so we have, we see for this location, we have location localhost 8332, and localhost 3000, because that's where our base app is hosted. Right now we have our listening port on 81 instead of 8080 because of reasons. Of course. Well not cores, but because there was something else running on 8080, I didn't want to mess with it. Good, thank you. You don't have to do that. All right. Oh yeah, I know what that is. Right. And then you can just, okay, I think the password, and there's no evidence of it on the screen, sure, fantastic. Okay, so it looks like it's already in use, if you actually, it's just the check, slash. But it is, we see that Internet is already running, because right now this is repointing to our, what's it called, our Bitcoin vServer, and now we're ready to run, now we're ready to run npm start, and if we do that, we should be running our app. But remember that we can't run it on 3000 because of cores, so if you do this, we're going to document, and we can sign, and we have a signature, we have a hash payload, and an address. All right. That's it. Fantastic. Now let's do the, let's do the, you're saying, so if you wanted to at the end like verify the signature you would. Verification has not implemented in here, because there's, we needed the, we needed the database for that. Oh right, right. Okay, no problem. Okay. But that, those are next steps, I'll write that up also. Cool. But that's it. It's a very simple demo, for now. Trust me, it works. We have verification on like other data sets, so we can verify on that. Like from this, from the end of the line, on the one we're doing, yeah, you can Json files and stuff. You can actually, if you sign this and take this, you can take the hash payload, use that as your message and signature and address, and you should be able to run. You won't, you won't be able to check that the hash is correct, but I mean. We can do that out of Banda with any, like, any algorithm, I mean any implementation. Yeah. Shot 256 common, which is great. So if you do, I think it's over here we have, check, some more validate message. Verify. Verify even better. Verify. Message. Okay. Wait, is it one word? I think it was. I'm copy this address. And it looks like we have to type this out because it does. Oh my God. One, two, three, four, five, six, seven, eight, nine, ten, ten, ten, ten, ten, ten. Why isn't it letting me see that? There we go. Okay. You can hide this too. You can hide this. Yeah. Okay. And then the console, we have. Nice. That's a good way to not have to type it. And then signature. This is our payload. Why is this doing this? True. Fantastic. Validate the message. Okay. So that I consider a complete victory. And thank you very much, Andrew Coe. You definitely earned the Brass Rat today. Thank you.


update. Good afternoon folks Steve Rhodes coming to you live in the shores of Delray Beach, Florida. This is your one PM update and currently we have a slightly mixed bag out here. That mixed bag is with the transports and the semis of just slightly. They're basically flat but they are just a slightly negative. The Dow's up 43, S&P's up 8, NASDAQ 157 points. The Russell 2000 is a big leader today percentage wise up about 9 tenths percent or 19 points out there. You've got gold up a half a percent. That's 9 bucks. Silver's up 20 pennies. That's 9 tenths percent. It's like to recruit up half a percent or 38 cents. Trading out at 76.94. Let's go spend a little time with our nine panel market update chart. We begin by take a look at the ES mini. That's in the upper left hand corner. Today is going to become bar number six of a TD9 count. So the only topping signals that we have because price is above all resistance levels. TD9 count areas, TAS market profiles. So the potential topping signal at the moment would be a TD9 count top that would take place sometime in the middle of next week. That's likely to occur because we have that spot volatility still below its 50 day expense moving average suggesting that it wants to target the lower Bolinger Band at 1527. NASDAQ 100 interestingly enough for the NQ has not taken out its Rosemont Dementicator top. That's the high from the trading day of November 22nd. That level would be 769.25. The U.S. dollar index you can see just consolidating within side its daily profile level. Gold as we talked about yesterday it has been able to stay above the top of its daily profile. That's an 1802. That suggests to run to the 1828 level. The case of silver. Silver already has a sell the D point pattern, but price may go target. It's high from a few days ago that bearish shooting started the 2346 level. Light sweet crude has got an A to B equal CD to the upside. What this needs in order to cement some type of the top would be a bearish reversal candle. Short of that light sweet crude should go target 7995. If we take a look at natural gas just struggling it has a by the D point pattern, but it is suspect suspect because price cannot take out that gap down resistance level of $3.98. And if we take a look at 30 year treasury, although it was trading just slightly below the bottom of its daily profile, you can see it found support at its little rising trend line. If you can't bust them down may try to bust them up in the case of the 30 year treasury that can be sending a signal that wants to make move to the 161.09 level. Folks, stay tuned for the Trader Zed Show. But if you're off to start your Thursday, have a terrific one. Have a happy new year and we'll see you soon.


So, I'm going to talk about image processing and about two tools, Scikit-Image and Dash, which I hope can help you to build very modular pipelines and applications for your own image processing needs. So, I'm a member of the Scikit-Image core dev team and the work on Dash which I'm going to present has been sponsored by Plotly, a Canadian company which I'm going to join in the fall. So, as you may know in the by-data community, images are a very common form of data and you have needs for image processing in various domains of science and industry. For example, in biology where you have microscopy images or for satellite imaging, quality inspection, but also for autonomous cars, for example, where you want automatic segmentation and so on. So, as you see, the needs are very different. They span a very large number of fields and in all these fields you have various tools which exist, some tools are libraries, some tools are user interfaces and all these tools are quite different. Some of them are written in Python and the tools I'm going to present today are not meant to cater for one very specific need, but rather to help you build your own image processing application when you have a specific need. So, let me start with Psych2Image. So, just out of curiosity, how many people here in the audience are using Psych2Image? Can you please raise your hand? I am. Okay, so some people, so please come and talk to me after the talk to tell me about all your bugs with Psych2Image. I will love that. So, Psych2Image is a generic image processing library. When I say generic, it's not for one application in particular, but its mission is more to process scientific images, rather than, for example, Instagram filters. It's really more for scientific needs. It's open source. All the content I'm going to cover today will be open source, BSD or MIT licensed. And it's for Python, obviously here at EuroPython, using NumPy Database as images. Compared to other image processing tools, one specificity is that Psych2Image works well with 2D, but also with 3D images. Sometimes with ND images, like in science, you have MOI, CT, a lot of modularities where you have 3D images. And last but not least, Psych2Image tries to have consistent and simple API and also good documentation, gentle learning curve, so that when you're getting started with image processing, you can get started quite smoothly and learn by yourself. So I'm going to cover this a little bit. In this slide, here's a short overview about what you can do with Psych2Image. So it's image processing for science, basically manipulations of images in order to transform them for other purposes, like when you want to filter them. Here you have a denoising example or when you want to extract information, like feature extraction for further classification. When you want to extract objects, this is called segmentations. Or after some processing, when you want to measure the size of objects, the shape that is to transform your images into numbers out of which you can do science. So this is what Psych2Image does, and this is what Psych2Image is not. It's not a deep learning library, I'm afraid. You have really great deep learning libraries with image processing capabilities, like Keras, for example, has some nice image processing examples. So the reason why there is no deep learning in Psych2Image is mostly because of architecture and maintenance choices. We choose to be a very maintainable library, very well integrated into the NumPy SciPy ecosystem, that is all the code is in Python or Sison. So there is no GPU specific code, for example. However, Psych2Image interacts well with machine learning and deep learning, both for the pre-processing and for the post-processing parts, where you can do normalization, data augmentation, or after deep learning, you can improve your segmentation, do some cleaning of instances, and so on and so forth. Also, one thing that we do not want to do in Psych2Image is to have a lot of very bleeding edge algorithms, like the one that you just published during your PhD six months ago. It might be a really cool algorithm, but if we do this, we'll end up with like 100 denoising filters, and then how will our users find their way through a library. We want to have a short API so that it's easier to find the functions, and therefore we let time do the Darwinian selection and choose the algorithms which we include. Psych2Image is a full-fledged component of the scientific Python ecosystem, and as such it works with NumPyArWaze, which are the images we process, and so it interacts also really well with... So this pointer does not work. Yeah, it's very weak. It interacts also really well with Psych2Learn, because you can pass NumPyArWaze from Psych2Image to Psych2Learn and vice versa, and also it interacts also really well with the visualisation libraries of this ecosystem, because once again it's this NumPyArWaze object, which is kind of the ling-waf ranka of the scipy ecosystem, which we exchange and pass between all these modules. So here is a very short glimpse into the kind of code that you would write with Psych2Image. I'm not going to make a big demo. You can find a lot of tutorials on YouTube, for example, but what you can see is that you first import sub-modules, so the functions are typically inside sub-modules. For example, the IO for input-output reading, an image from a file. This image will be a NumPyArWaze. You see here I'm asking for its shape. And then the syntax, the API, is that you have functions like this thresholding function, which take as input NumPyArWaze, and they return either numbers or filtered images, which are once again NumPyArWaze like this function, for example, which measures the connected component from here binary image to connected component. The input is an NumPyArWaze, and here the output is an NumPyArWaze, as you can see here. So the NumPyArWaze has actually all that we need for image processing, because pixels are just array elements. And so our API is really only functions working on images and returning images. The first argument is always NumPyArWaze, and then we have optional parameters, which are keyword arguments. If you want to tune the behavior of your function, we try to have sensible default values. Also here I have an example with a 2D image, which does this block of code, but it would work exactly with the same syntax if you were to have a 3D array, because we have exactly the same syntax. So pixels are array elements, and it allows us to use all the machinery of NumPyArWaze. So here it's just pixel indexing, changing the values of pixels, accessing to a channel like RGB image. It's a three-dimension image with three channels, but you can do also masking, fancy indexing, and so on. So the API is simple. We have just sub-modules, and these sub-modules have functions taking NumPyArWaze as input, 2D, 3D, sometimes ND, and the output is a number or an array. For the API, through time we have converged to a quite consistent API. If you started using scikit image like five years ago, maybe it was a bit more chaotic, but now, for example, all the denoising filters start with denoise, so that you can try to discover new functions, new filters, just by browsing the API and looking at the dog strings of these functions. I will show also the gallery, which is another way of exploring scikit image. We try to be consistent also for the variable names and also inside the code, for example, how we name indices, something as stupid as, are you using XYZ? Are you using plain row colon? We have heated discussions on the GitHub to try to find some consistency for this. Here is a short example to show you that scikit image and scikit-learn interact really well. It's an image that I acquired for my research with my team, so it's a grain of gypsum that makes the plasterboards and part of it has been dehydrated, the part which is textured and part of it is still intact and we wanted to do automatic segmentation of this. For this, we extracted features using the feature sub-module of scikit image in these two regions, and after we fed these features to a random forest classifier of scikit-learn, it gave us a first segmentation, but it was not really good, so it had a lot of mistakes. We cleaned this segmentation using traditional image processing like Gaussian filtering, thresholding and mathematical morphology. It's to show you really quickly this interplay between machine learning and image processing. A few facts about scikit image. It's released 0.15. We have more than 200 contributors, but between 5 and 10 maintainers, so we really try to welcome new contributors and I would be happy to talk with you if you could be interested in contributing to scikit image or reviewing for requests and we always need a lot of enthusiastic people. Our community is quite large. We have 20,000 unique visitors on the scikit image website, scikitimage.org per month. That's how we estimate the number of active users. If you go to this scikitimage.org website, you will find one of our most beloved features, which is the gallery of examples, which allows you to browse through thumbnails showcasing image processing applications and you can select one and open an example. I would like to give a brief shout out to the underlying package of this gallery. It's called Sphinx Gallery. If you're building your documentation with Sphinx, you can just import it as a Sphinx extension and get such a gallery just from Python scripts. Here is one rendered example with the code, the image generated by the code, some explanations. The gallery of example is really the part of the scikitimage website, which is visited the most because our users will come to the gallery and say, I want to measure the size of images, the size of objects in an image and they will do like control F on the gallery or something like that and open an example. We also have a CC also sometimes between examples. Sphinx Gallery also gives you nice features like at the end of the doc string in the API documentation, it will create mini galleries like this one with all the examples using a specific function. This comes for free when you just import Sphinx Gallery and also in the examples you have links to the API documentation. It's a lot of redundancy, cross-linking between the different parts of the documentation and it helps your users not to be lost in some dead end somewhere in the documentation. I really recommend giving a try to this Sphinx Gallery package. Let's say for example that you want to denoise an image, this is an image that I acquired during one of my experiments and it was very noisy. How can I denoise it? When I go to the gallery, there is an example showing how to denoise with several different filters. One shortcoming for gallery is that at the moment it shows mostly pictures like cat pictures, cars pictures, pictures of people and we miss examples with real data sets but we are working on this and if you have a good open data to contribute, we might be interested. There were explanations about all these different filters and here you can see, that was on my image this time that just with one line of code I can try one filter tuning the parameters with keyword arguments and you can see that from this noisy image for example when you use quite specific filter which is this one, the total variation filter, the histogram gets really peaked. So you can start having good results with very generic filters like the median filter here in green but it gets much better when you try the more advanced one. Of course sometimes at the cost of longer execution time. Something which we want to improve in the future is the speed of execution and the parallelization because some other packages use GPUs for example but we use only NumPy code once again for maintainability so in the future we want to experiment with NumBar and Python for example but at the moment what we do is chunking it into blocks. So I would like now to go to the interaction with the images part because why do we want speed execution? It's because sometimes when you do image processing you don't really know what the workflow will be, what the pipeline will be and then you need to tinker a bit with your images you need to try different parameters and for this for example you can use the widgets so here for example I have used the IPI widgets package and it's an interact decorator and if I want to choose the best Gaussian filter width I can just use the slider and select my best parameter you gain a lot of time by having this kind of interactivity and this you get with widgets but sometimes you need another kind of interaction with your images that is you don't want to change the parameter generating your image but you want directly to draw on images for example to have markers for the segmentation to identify an object to be removed from the background to delineate roads on a satellite image or to have bounding boxes for a training set for further classification and for this we have developed this dash canvas package I will give you one example which is this tool which is integrated into web applications thanks to the dash web application framework so you have the different components of the web application here I can increase the size of the brush I can change the color and so on and then I can perform a segmentation based on my annotations so on this annotation tool I have other features like rectangle, lines and so on and so forth so what is this tool? first of all the web application framework here is called dash it's developed by Plotli and the tagline of dash is no JavaScript so it's a web application framework in which you write only in Python and so all the components I showed you before are Python code I will give a few examples and it can be quite heavily customized so that you can really tune the layout so dash uses a flask server to run the applications and also all the components are based on the React JavaScript framework so there is JavaScript behind the scenes but the principle is that you write only Python and I have a few examples of dash code so what is that? no it's here so here I'm using the JupyterLab extension for dash so you see that I write some Python code here and when I execute it I have my reactive graph I have this radio items buttons here and each of these elements is defined in the layout here and when I want to add some interaction between these elements I can do this using the callback decorator of the app of the dash app and when I do this when I change for example the value inside this textbox then this text paragraph is also changed so this is defined here in this callback mechanism and if I go back to here to my app for example then there is this in the dev tools of dash you can see the graph of callbacks which is a bit more complicated because I have more elements but it's exactly the same principle as my little examples so which components can you use in the dash apps? you have the normal HTML elements which are provided by the dash HTML components the reactive components are found in the dash core components for example the sliders, the drop-downs, the radio items I just quickly showed you have also reactive charts plotly but not only plotly charts so if I go back here for example I have one graph and just clicking will populate the hover data I can select also which will change this part and it's quite classical to have figures which can be changed for user interaction but here it's a user interaction with the figures which modifies other components which is a bit more tricky to do you also have interactive data tables which you can include specialized libraries for specific components like for engineering or biology and basically every time you have a React JavaScript library you can wrap it with dash and this is what I did for this dash canvas package there was a very neat JavaScript package called React Sketch and I just wrote a wrapper around it adding these little buttons and this is how it was quite easy to create a dash canvas package so dash provides you two things one of them is the dash canvas object which is a modular tool for annotations and selections so you see here some sample of such annotations and also you have functions to transform these annotations that is to make for example numpy arrays, masks out of these annotations which will be then processed by scikit image dash canvas depends on scikit image so for example this is how I could use these annotations to do the segmentation of these objects in the demo if you're interested there is a gallery of examples on dash canvas.plotly.host I can show a few examples of this so here is the gallery you have one example with just bounding boxes and then populating a table, a numerical table like when you want to build a training set for machine learning there is one example in which you want to remove the background from just one person and then what you do since it's not perfect you can just improve it that's really the benefit of interactivity and so on and so forth so I think I'm running out of time so I will wrap up so this was a quick introduction to dash canvas which is quite a new project it started at the beginning of this year the roadmap which we have is to improve the interaction with images having for example annotations which can be loaded from a given geometry from a file and not only from the user drawing the annotations also annotations triggering directly callbacks without having to press a button and I would be very interested also in handling 3D images and time series for example for segmentation of objects in 3D like what you have in the medical sciences adding more examples for the gallery as well and since this interactive component is based on JavaScript it could also be useful for other packages like some libraries using widgets and so on so we can talk about it if you're interested so thank you very much feedback is very welcome on these two tools scikit image dash and dash canvas and please be in touch, thank you Any questions? Feel free to go to the microphone please Hi, thanks, it's very interesting when you added a little interaction from this input field and showing the text when you change the input field does it actually go through the server and back to JavaScript or does it all happen on the client? It goes through the server I think let me... yes, yeah you don't have computations done like on your local machine so I didn't speak about deployment like the app which I was running with the segmentation of the cells actually the server was a local server on my machine this you can do, you can also add the apps to an existing Flask application and you can also deploy using G Unicorn for example on Heroku and so this is the only commercial part Plotli also commercializes deployment solutions for that application, that's a business model around dash which is otherwise completely open source Hey, thanks can you tell us more about the medical images what are the challenges that Scikit images has regarding these type of images? The question is about medical images Yeah, exactly So for medical images we have identified several challenges one of them is to add more examples using real life science data sets because sometimes I go to conferences and like a biology person will tell me oh I never thought that Scikit image is for myself because I never saw a cell image on the gallery for example so this is one thing which we want you to do also a lot of 3D images are quite large data sets like acquired automatically with I don't know Lightsheet, Microscopy, CT and so on and for this improving the speed of execution through automatic parallelization is really something which we want to improve and also the dash canvas part it's not Scikit image there are people in common between the two teams but it's something which I see on top of Scikit image really adding some user interaction to play with images to annotate them so I also see this as something which can be useful to the life science community because you have a lot of people using like imageJ to do measurements or to do just manual segmentation and this you could do with Scikit image and dash canvas as well okay thank you time is over so now 5 minutes and we start again at 35


All right, welcome back cyber traders. It is Tuesday. How's everybody doing on this lovely day? Got two more days until Thanksgiving. And let me tell you, it has been a great pre-market today. One of probably the best pre-markets I've seen in months. How's everybody doing? So a lot of good stocks are making some big moves. We had a really big winner today. I just want to point out, my God, the F-Tech, are you kidding me? F-Tech, we were trading F-Tech at a dollar. And not only has been a good day trade, it has been a phenomenal swing trade. Stocks up 600% in two days. Unbelievable stock did great. We're going to talk a little bit about that. We're going to talk about what happened, also what happened yesterday, because yesterday, and you know, Josh actually brought up the point yesterday. Mondays are usually not the greatest days. And we actually had a great Monday. I mean, we had a great, great Monday, shockingly. So let's go check that out. And then we'll go through the watch list because let me tell you, we got a big, big list for you today. And let me tell you, there was a lot of stocks that were in the pre-market that obviously went from the A-list to the B-list. And there was a lot of stocks on the B-list that now hopped over to the A-list. So let's go out there and check that stuff out. And I just want to start off what happened yesterday. First of all, this F-cell has just been a monster, monster. Stock went to $10. I mean, anything that has to do with fuel cell energy or anything, first of all, could you guys just think about this for a second? Why do you think? Why do you think all these NEOs, Nikolas, all these stocks are moving? Could anybody have any, like, any type of recommendation? People, anyone on YouTube, Facebook? Tell me, what do you guys think? I mean, and I'll tell you why it is. Why do you think it's going up? Biden? Right. So what did I tell you? You are going into a market right now that you're going to have a totally different ideology of people, where they want to take the economy and certain markets are going to thrive and some are going to get crushed, OK? So if President Trump won, you have the same policies. Now you're going to have President Biden and you're going to have different types of policies coming in, so everything is moving. So if it's wind, if it's electric cars, whatever it is, I mean, remember, you might be a fan of him or you might hate him. You might be a big fan of Trump. You might hate him. But at the end of the day, we are all part of the same party and we are the trading party.  But don't let opportunities like this go by. Like I had a friend the other day, he's like, wow, riot? My god, why is it going up so much?  So that whole thing, especially new transitions going on, you're going to see a lot of things change. Also, what are the other big things that are going on right now? You know, we're looking at all these stocks and it's not just the presidency that's taking off. There's a huge, huge short squeeze in Tesla. I mean, Tesla, you forget this did a stock split. You did a stock split? When did it make it? Less than what? When it made that big run up was in September? Look at the stock. Now they're saying to probably go to 1,000. I mean, the stock was $100. Tesla is the basic, what do you call it? The kingpin, I would call it, of all the other stocks because they're all following suit. So when you look at it at sell and you're looking at all these f-tex and all these stocks have something to do with it, a lot has to do it because the granddaddy of them all. So everything is just spooling in one to the other, one to the other. And let me tell you, now they're saying that if they don't come out with a stimulus package or do something that we're going to have over a million and a half people unemployed by January 1st, there are going to be so many people that are going to be getting wiped out of their unemployment. And for all the people out there that are worried about unemployment, guys, could you start a new career? Just could you please stop focusing on like when they were worrying about the $1,200 stimulus check and I was telling you, you really think we really care about $1,200? We do care about the $1,200 stimulus package for some of us. But when you come into the year and you see what's going on, like I had somebody the other day was worried about spending to be part of the cyber group room because it's too expensive. So listen, if you think this is expensive, you should be trading period. But you want to make some serious money. Where are you going to find a stock like Riot when it goes from three to seven in three days?  You're really worried about $150. You're really worried about being part of a program for a year and paying $10,000 when you make it in almost in one day. But you want to worry about getting that stimulus check. Trust me, don't let government hold you back. Go out there and let's start, let's capitalize on it. Like it or hate it, this is, I mean, people like, well, I can't afford to trade the market because, you know, Facebook is trading at 270. I'm like, who's trading Facebook?  You know what I mean? There's so many stocks out there that were killing it.  F cell was one of them. Okay, what else we had DPW for crying out loud. That figure ran from two to eight was not even stopping period. Unbelievable, PLTR for crying out loud. New wide PO, another one, $10 to 21. Now it's, look, that's making, you know, testing a new high. Another stock, by the way, I got to put that on the B list. PLTR.  NEO? Okay, NEO is $3. Remember that stock we were trading that back in May and April? Okay, look where it is now, 50, oh, 58. Another, you know, I always make fun of them. Copycat Tesla, but you know what? Who cares? You made money. Oh, these people are just Chinese. They're trying to kill us. They're trying to, you know, that copy everything we do. I know, whatever, but don't let that affect you to not make the buy the stock at three. Now it's at 55, 58, you know? I mean, Nikola, which I'm a big fan of it. Look at Nikola, guys.  I averaged up. We all remember trading this stock when it went to almost 100, right? And it took a big hit. The only difference with Nikola, it's in the hydrogen business, not in the battery business. But I'll tell you, I don't see resistance. The next resistance in Nikola is at 35. A lot of us own the stock at what, 22? And that was only, what, five days ago? What are we up right now? We're up almost, you know, almost 10 bucks on that stock. I'll take it. XPEV.  Look at this thing. November, $20 to $72. Yeah, you're still worrying about that next unemployment check. Time to change careers. Worrying about the social security check? Time to change careers. Listen, people living longer, don't worry about that.  Remember, trade small and trade often. Now, this is all good, but there's only one issue. You have to learn how to do it, right? So today is a very busy day. And I know we did class yesterday for all the golden platinum students. I mean, the classes are up there. Josh did a phenomenal job.  But today is also gonna be a busy day too. So you got traders talk at 11 o'clock and then you're gonna have me on timing research at 12. Don't trade in the middle of the day. Go out there, let's make our money within the first hour and let's ban, let's go right into it, get into class because you have to learn before you could earn.  So you better be there because that is the most important time that you should focus. Don't, you know what? If you missed this morning because you gotta go do something, you know what? Don't worry, stock market's not going out of business but you gotta be in class, all right? So anyway, let's talk about some of the stocks that are moving. Kramer's chatting up Nikola on CNBC. He loves, you know what? William, he ran it up last time. He ran it up last time, you know? And when you opened up his mouth about it and that was the last pop. So, you know, and Excel has a lot to do with it, remember? So listen, you gotta pick your fights. You know what I mean? What are you gonna do? But anyway, let's go through the watch list because we've got a big list right here. I'm gonna start with the A list, okay? So there was a lot of stocks. Actually, I'm gonna start with the B list because the B list was actually, a lot of them were moving pretty good this morning and then all of a sudden they backed off.  This thing just literally, we traded a dollar with a 280. Look how much it gapped up right there. Actually put a five minute chart so you guys can see a little bit better. Look at that. After hours, the thing just took off went from three, all the way to five and it popped and had a huge run in pre-market. If you were here when you were supposed to and you heard me say it all the time, early bird gets the money. You were there, you did well with F tech. F tech. And also yesterday. OPTT also. Look what happened after hours. 220 to 320 after hours. All the way up to like the middle of the night and it also's gapping up big again. It's testing some resistance levels though in the beginning of October, so be careful of that. SPI, we all know SPI. Remember we traded it yesterday? And guess what? That was the stock that was probably hands down and I told you this yesterday. The best trade of 2020. It went from $5 to $50 in one day. It was chaos, it was great. But anyway, she's starting to back off a little bit. Be very careful of that stock. It's a huge store, a short squeeze. IDEX, this stock, you know what? It was on the B list. I'm gonna move it back on the A list. Another stock that we've been trading with did well. Great yesterday, great after hours and it's continuing what happened yesterday. Mara, another one that we traded this morning. Did great yesterday, went from three to five and this morning, boom, gapped up, it's only to six, okay? Overnights have been great so far. You know I'm not a fan of that, but you could trade less and trade off than doing it. And then obviously the PLTR, we already talked about that one. That thing is just, you know, it still hasn't picked this battle. Okay, let's go hop on the A list. This stock right here, AREC. This stock had a really nice move and other big short squeeze. It was great this morning. I actually also did pretty well with this stock. You could trade a lot of shares of it. Got a little nasty with some shakes here and there, but also, let me just fix this chart right here so you can see it a little bit better. You know, if you jumped in right around 830, it had that $2 support levels, 50 cent pop right there.  I wanna see how it opens up. Listen, the markets not even open. That's the funny part, okay? BRQS, another one that's up 13%, 4.7 million shares. Got some nice iceberg orders out there.  So I'm a little concerned about that one. We'll see how she opens up. Same thing with MG, GSM. Stock has been great the last couple of days, but also the stock obviously, it peaked out here around 845, around a buck 80 stabbing down at 140. So we're gonna probably throw that back on the A list. Tesla, I'm just gonna bring it up. You know we're not trading it, but this guy is my age for crying out loud. He's the second richest person. I'm just wondering how much longer he's gonna take him to be the richest person in the world, in the world, okay?  And let me tell you, I don't see any and losing any of it, all right? And then obviously Nikola is doing great too. We already know about that one, which obviously he's following suit with it. And I guess when you brought it up when William, when he talked about it, that's where he made his big pop. All right, so Norm, you made about 14 cents on rig. There you go. That one's, you know what? I've got to put that on a watch list. Yep. R-I-G, good call. All right, nice. Nice. All right guys, I'm sorry to go at a little bit of a tanger right now, but it's just been a great, great morning. And you got Thanksgiving that's coming up. You got about two days. Let's go out there, make our money quick. Just remember, everybody, trade small. You don't have to get crazy on certain trades.  If you're one of those people that got into a little bit of a hole, because I know that happens to some of us sometimes, that happened to me actually yesterday.  And it got me in the negative. I had to work my way back to make my money back. Listen, you know, this is what I'm gonna talk about next week. Try not to double and triple down, okay? Try not to double and triple down.   That hole becomes a lot bigger and you don't want to do that. So it's the tip of the day. All right, so don't forget class today. You got traders talk at 11 and you got me on timing research. So go out there and support us, register for those events and we'll see you back. And for everybody else to see back here at 2.30 for the afternoon meeting. And if you've made your money, see you back here tomorrow morning, right here. Good luck, everyone. Happy training, be safe.


Welcome back folks. I doubt I was up for 64 Nasdaq's up to 49 SAPs are up 52 Let's go over to our mammoth the teddy cakes that as we do each and every Wednesday at 40 past the hour You can reach Teddy every trading day at 4x dash trading dash unlock calm That's 4x dash trading dash unlock calm Teddy cakes that what's going on brother? No, it's a quiet Wednesday as we're waiting on the Fed today. Yeah, so the bottom line is that What can we expect out of the Fed right? Well, I think it's more of the same, you know, it's quite honest with you And you know, we've been talking about how the volatility has been slowly dropping over the past few weeks And how we've been kind of looking for this to kind of stabilize a little bit And I think we finally hit that flat line point now if I mean if you look at their major currencies versus the dollar Like the pound the yen They're besides having tighter ranges on a daily basis, they've really gone nowhere over the past two weeks They went from wedging to just complete consolidation Now this is the majors, you know, like the pound the Swiss that the euro But when you still remember we we've been talking about a lot of your lesser currencies like the Turkish lira I can pay so, you know, like I think that the bull is still there for the dollar on but it's starting to slow down I think that it's topping, you know in a lot of those currencies The peso for instance their coronavirus pick cases have gone up Not in a good way over the past couple weeks But the market itself has consolidated in the peso for the past like month or so So I think that we're pretty much at the extreme now with the go with a lot of the lesser currency crosses So your dollar strength I think is holding up because of that, you know So and the dollar index remember when we spoke last week the dollar was still on a little bit of a bullish path And we were looking for it to kind of die out and start to hit at the upper part or the lower part of a resistance zone It did and if you look at like the dollar index chart and the euro in versus the dollar or the pound versus the dollar Canada all the big ones they're all starting to look like a reflection of the dollar index chart either directly or indirectly Depending on the gun, you know, which side the dollar is on and so this is what we've been looking for and talking about for weeks that You know the market has absorbed all this stuff and remember we talked about the interest rate component a couple weeks Back about how that's pretty static and frozen. So today we have a Fed day. What is the Fed gonna do?  Well, no, it's because of the value of versus taxes inflation and what have you We're already at zero. Where are they gonna go? You know, so I think that all they can do is give more, you know Propping up saying that you know, we're gonna keep on to supporting the bond market keep on doing these things until we get Through this wave, you know, so And I think that's really where we're at kind of in limbo.  I think I think it's too overdone, right? I mean, yeah, right Yeah, right, right and I think that that's exactly what we've come to that point is that I mean Let's just say that the the coronavirus curve doesn't go up or down over the next month or so What difference does that have to do with the markets now? They've already had the shock value We went through that two months ago. You know and if you take coronavirus aside Let's just remove that from the equation The dollar was was a bull that was starting to struggle at the end of the year going into this year So if we take the coronavirus part out as we start and flatten the curve and come out then by just Going by that scenario the dollar should retract, you know But I think in the short run right now since we still have a lot of Unclarity, you know an uncertainty rather that that's what's holding the dollar up because it's still a flight to quality You know, everyone is still looking for the US dollar as support everyone's still looking to America for as a leader You know, I mean we have Europe that's starting to come out You know, we're looking at the numbers from Sweden and Norway and how things are How things are working over there in other parts of the world and if these models are actually correct And the real as we get more testing if these things start to really show the real Validity of where we're at now see two months ago. We was too much ambiguity. Right now We have data we have actual numbers to look at, you know And it's actually starting to fall into place more and more and more and if this trend continues Well, then our baseline should be where we're at now We'll stabilize and we'll return to where we were before the corona virus, you know As far as currencies and interest rates and things the equity markets. That's a whole nother ball of wax Yeah, it's so intriguing man that you know, we're so lucky that the dollars reserve currency of the world because if any of the country ever Used this much stimulus we would I mean I could just picture us saying what are they doing man? I mean they just the printing below the digital presses are going we don't even have printer presses anymore folks We do but the reality is that the central bank just hits a button digitally, you know Bottom line if Teddy owns the bank, you know, I'm the Fed Tommy's the Fed you hit a button and all of a sudden, you know You get a trillion dollars in your account that you can start lending out, you know what I mean? So right it does get pretty wild watching this whole thing shake out No, no, we'll think about the value of the dollar. I mean, we're one of the world's food producers Could you imagine if we were in the opposite relationship and our currency was slammed and come out of these were low? I mean you could have China basically buy up our food supply and we'd have starving Americans. Yeah, that's It's a big number. There's this. Yeah, I think we're all gonna basically find out quite a bit About many different things particularly, you know about what is what is the value of A food chain any type of chain actually, right? Do you know I'm saying in general, do you know what I mean? And then of course the dollar the dollar is a big one man I mean is sure I think folks that even well I it's hard to comprehend actually, you know as to how you can actually push that much money out and The doll is still holding but I can understand it because even though Europe can't get it together yet these These first-world companies are gonna have to push money out so the whole thing doesn't collapse, right? Because then they're gonna collect anything, right? Yeah, correct, and we will have a retraction the dollar We don't want to have the dollar as strong as it is right now This is a short-term thing that's good for the world good for the US But we need to have the dollar retract over the next like six months to a year. This is not a sustainable thing for the dollar It's not good for us. No, well, it's interesting.  So and there's more room to the upside with gold and there is with the dollar Yes, you know, I mean when you look at the index like people who don't aren't familiar with the dollar index or what? How that gauges the value of the dollar don't realize how expensive the dollar is right now, right? I don't know. I'll tell you good if we run vacation would realize how powerful it is wouldn't we? Yeah, you go to Mexico go to Brazil and you'd be a multi-billionaire man. Yeah, right Hopefully we have some signals for you next week. So you have a great week safe week. We look for speaking the next Wednesday Thanks, you have a good one guys. You too. Stay right there. Tell me not come right back folks