Hey everybody, welcome to the second ever edition of my most anticipated manga releases. This time for the month of February. Pretty exciting. Now, a couple things. This is the second time doing it, so I'm still perfecting these types of videos. I don't want to highlight, like, for example, Urusei Yatsuda is coming out at the last volume. I can't really recommend that, because I'd be asking people to, oh, you want to get this? Then you need to get like 16 other books. So I'm mostly focusing on volume ones or collector's editions or hyped up releases and stuff like that. So here are 12 manga that are coming out in the month of February that I think are worth checking out. Let's get started. First one on the list, Shoha Shoten. I did a video on this manga when it was first coming out and I quite enjoy it. It's written by Akinari Asakura and drawn by Takashi Obata. Shoha Shoten tells the story of young Azamichi Shijima who has secretly been practicing to be a comedian. His classmate Taiyo Hiyashikata also has a similar aspiration, so it should be no surprise that these two are bound to team up to take the comedy world by storm. One event or venue at a time. Shoha Shoten has wonderful art and an out of the ordinary premise for a jump square title. The dynamic between the two lead characters is great and I thought the jokes and humor translated pretty well into English. Also noteworthy, each volume of this series only contains three chapters. But fear not, they are twice the length of a regular one so you aren't really missing out. If you want something a little bit different, be sure to grab this for your collection. Box head time. You got Wotakoi. Love is hard for Otaku. It's finally being released. It's been delayed multiple times. In this format, you'll get all six Omnibus editions of the series plus an exclusive sticky notepad. If you don't know what the series is about, in it we follow Narumi and Otaku in hiding thanks to her previous dating experiences of men dumping her after she has revealed her secret. After a chance encounter at her job with her childhood friend, Hirotaka, who almost exposes Narumi's secret, she comes with a counter-proposal. Why doesn't she just date him instead? This rom-com from Fujita is a favorite of many and has received an anime and live-action adaptation in the past, so I'm sure it will sell pretty well in this box-head format. Break of Dawn from Tetsuya Imai, the entire story in one volume. In this sci-fi story, we follow a young kid named Yuma in the year 2038 who is obsessed with the return of a comet. But on a particular day, while sneaking onto the roof of an apartment building, he finds something grander and not of this world. Now Yuma and friends must work together to uncover a secret that has been slumbering on Earth for years. This manga received an anime adaptation last year from Zero G Studios, if you're interested in checking that out, but if you're a sci-fi fan, I highly recommend picking up Break of Dawn. Marmalade Boy Collectors Edition Volume 1. The long-out-of-print 90s shoujo manga written by Wataru Yoshizumi is returning thanks to Seven Seas Entertainment. The manga was originally put out by Tokyo Pop back in the early 2000s, fast-forward to 2023, and we've got an upcoming prestige release for this beloved classic. Endensing the original eight volumes into six oversized editions. If you don't know what Marmalade Boy is, we follow the story of Miki Koishikawa as her parents decide to move in with another couple, turning Miki's world upside down. Now in a house of four parents and a cute step-brother, Miki isn't exactly thrilled with her new situation, and though she finds you cute, he's also kind of a jerk. Confessions of a Shy Baker, a slice of live BL romance by Masaomi Ito. The story centers around Toshimitsu Yamamura, who runs a real estate business, and Genta Tsubakisaka, a caregiver, both live together contentedly. In his spare time, Toshimitsu loves baking and making candies, and coincidentally, Genta loves eating them.  While I was preparing for this video, Confessions of a Shy Baker caught my eye for its simplicity, wholesomeness, and acceptance. The artwork is breezy and fun to look at, and the attention to detail with the sweets is sure to win readers over. Chojin X from Tokyo Ghoul creator Sui Ishida, two high school students that get involved in a tale of heroes and monsters, helping out the survivors of a plane crash. Tokyo and Azuma are attacked by a superhuman mutant called a Chojin, supernatural beings with powers stronger than your regular human. In the scuffle, the duo are forced to inject themselves with a mysterious drug that turns you into a Chojin. However, Tokyo is the only one that exhibits any side effects, becoming a monster himself. This is a dark, humorous horror story that has great artwork and perfect for fans of Tokyo Ghoul. Mermaid Scales and the Town of Sand If you have been following my channel, you may be aware of my fascination with the supernatural, the folklore, urban legends, and yokai, all that cool stuff. In this case, it's a manga inspired by Ningyo or Mermaids. In this story by Yoko Komori, we follow the character of Tokiko. Her parents have recently broken up. She and her father have moved from the city to a coastal town to live with her grandmother. As Tokiko begins to live out a new life in school, certain memories start to surface that may involve the ocean and getting saved by a mermaid. Again, if you enjoy stories of the supernatural kind but with slice of life elements thrown at you, you'll be right at home with mermaid scales. There are many books coming out this month, but for me, I would say this is my hyped release of the month. Sweet Poolside by Shuzo Oshimi is a short story about two middle school students in their swimming club. The story follows a brief moment in their youth where puberty and body hair take center stage. Ota is a bullied, hairless young boy, while Ayako is the opposite with her abundant hair. That's stranger when Ayako has the most unusual request for young Ota. Now I know it sounds odd, but Oshimi's work deals heavily in the perversion of innocence, first loves, youth, coming of age stories, that sort of thing. And I'll be frank, this isn't Oshimi's best material in terms of art. And the story will probably leave you wanting more, but I do recommend checking it out as I think it's one of his strongest one-shots that he's created. The Snake Who Loved a Sparrow by Enna Natsuo. This supernatural romance BL is about a sparrow named Komazu that is fearful of snakes. Until one day he is saved from a rampaging boar by a white snake named Shirato. The sparrow lashed out in fear but realized he probably misjudged the snake and decides to befriend him. Fear and natural prey coming from different species and social classes can love overcome the laws of nature despite the differences in their way. You can find out with this release from Tokyo Pop. The art is pretty damn good in my opinion and I enjoy when someone can take stories and mash them together to create something unique, such as the case here with the snake who loved a sparrow. The second box head for this month goes to Don't Toy With Me Miss Nagatouro. The famous rom-com is being collected by Kodansha in box head form with the first six volumes here and a bonus item. The time of the recording I still don't know what that bonus item is so it could be a sticky notepad, it could be a poster, it could be a guidebook, who knows. Nagatouro is a freshman in high school who loves teasing and torturing her older male classmate. What is her motivation and why does Senpai put up with her? Does Nagatouro just want to create misery for Senpai or maybe she secretly likes him? Box heads have become increasingly popular over the years so I have no doubt this will breathe new life into an already popular series and sell pretty damn well. A Home Far Away by Teki Yatsura. This drama romance BL is published by Kuma, follows a young man in 1990 named Alan who is currently lost and searching for direction in life until he meets Hayden, a free spirited cook. Alan may not know where his life is headed but at least now he has someone to lean on. Filled with new feelings and many new challenging experiences may force Alan to find his path on the road. I don't know about you but I happen to enjoy period pieces and media, books and films that take place in the early 90s are of interest to me plus you add in the detailed artwork alongside this story of self-discovery and romance, he got me hooked. I'll probably check this out. Finally for this video, the invisible man and his soon-to-be wife, another quirky rom-com mixed with the supernatural. This one follows a quiet and bashful woman named Yako working at a detective agency. Tonome, her boss, is kind, dapper, and quite the gentleman, except that he's also invisible. That ability might be perfect for work but dating and romance is another matter entirely. Yako is blind and can sense when he's around. This manga has a fun twist on the invisible man with more of a slice of life slash romantic comedy aspect. It has the charm, fantastic character designs and some really nice colored backgrounds. I highly recommend checking this out as well. So there you go, 12 releases for the month of February. Now there are a lot of books coming out, I couldn't get to them all, I just wanted to put out 12 that I think are really neat that I think you'll probably dig. But if you have other suggestions, other picks, let me know down below in the comment section what you're interested in getting. Thank you everybody for watching this video, that's gonna be it for now. Thank you to all who liked, subscribed, and shared and all that fun stuff. A bunch of new people jumped on board and I'm super happy about that. Thank you. I hope you enjoy the channel. We've got much more content coming up so stay tuned for that. That's gonna be it for now. Thank you once again, God bless, stay safe out there. I will catch all of you on our next video.


Welcome back. We have been discussing thermodynamic functions in terms of canonical partition function and hence molecular partition function. The various thermodynamic functions that we have discussed so far include Helmut's function, enthalpy, pressure, entropy. Today we are going to discuss another very important thermodynamic function that is the Gibbs function or Gibbs energy. In chemistry whenever we talk about spontaneity of a process the first question the first answer rather that spontaneously comes is that a process will take place spontaneously if the value of delta G at constant temperature and pressure is negative. Please note if we just say that the value of delta G should be negative then the process is spontaneous then that answer is incomplete. The constraints must be specified that is for a spontaneous process delta G at constant temperature and pressure should be negative. Similarly, whenever we talk about the spontaneity in terms of properties of system alone we need to provide the constraints. For example, if we talk in terms of Helmut's function delta A at constant temperature and volume should be negative for spontaneous process. So, therefore, it is important to specify the constraints. Today we talk about Gibbs energy or Gibbs function. How do we define Gibbs energy? The answer to that comes here that Gibbs energy is defined or Gibbs function is defined in terms of enthalpy and entropy. If someone asks you a question what is Gibbs energy or what is Gibbs function the straight answer is that Gibbs function or Gibbs energy is G is equal to H minus T s. As usual this G H or S these are system properties. Now sometimes we transform an equation into another form which is more useful in the sense that the properties that we want to discuss or the equations that we want to establish become easier. For example, here when I say G is equal to H minus T s I can write H equal to U plus P v this is for H minus T s is already there. So, now the new form of this is U minus T s plus P v I am just rearranging it. So, that we can recognize this U minus T s which is Helmholtz function that means I can now define G also as G equal to A plus P v. We have now Gibbs function in terms of Helmholtz function and pressure and volume. Keep in mind that the changes in Gibbs function and the changes in Helmholtz function provide very important information. Revisiting that the change in Helmholtz function is a measure of maximum work that you can draw from a system and the change in Gibbs function is a measure of maximum non-pressure volume work that you can draw from a system. And here you have an expression which can connect both delta G and delta A and the connectors are these changes in pressure and volume. All right now on the same lines that when we want to connect with the canonical partition function we usually will refer to the zero point value. For ideal system for ideal gas P v is equal to N R T. So, therefore I can write G is equal to A plus N R T or G at absolute 0 is equal to A at absolute 0. Why did I do this? Because as I have always been saying that when you want to derive certain equations you may take a route which gives you that equation easily and in this case if I use the properties of ideal gas I am able to establish this that G 0 is equal to A 0. That means, now I can write another equation that is G minus G 0 is equal to A minus A 0 plus P v I am just connecting this with this this G and look at when I write with reference with reference to their zero point values. Now what I need is if I want to now connect this G with canonical partition function then I need an expression for pressure and I need an expression for volume. Remember that we already have derived an expression which connects A with canonical partition function and which connects P with canonical partition function and what are those equations? Let us take a look at A minus A 0. We have already derived is equal to minus k T log Q k is Boltzmann constant T is temperature in Kelvin and Q is canonical partition function. We have also derived an expression which connects pressure with canonical partition function here pressure is equal to k T into partial derivative of log Q with respect to volume at constant temperature. So, now if you substitute A minus A 0 value over here and pressure expression over here what you get you get is this expression G minus G 0 is equal to minus k T log Q plus k T v this v volume comes from here into partial derivative of log Q with respect to volume at constant temperature. So, here we have expression which connects G with capital Q which is canonical partition function and hence for a given system we need to establish whether the system consists of distinguishable molecules or indistinguishable molecules and then we have to use this expression accordingly. Now, as I said that A and G they are very useful thermodynamic quantities because not only delta A and delta G give information about maximum work or non-pressure volume maximum work available from the system, but the changes in A and the changes in G can give you lot of information. For example, let us have a short discussion. If I start with A, A is a Helmholtz, A is Helmholtz function or Helmholtz energy A is equal to u minus T s.   T d s T d s cancel. So, I have d A is equal to minus P d v minus s d t. As discussed in the previous lecture probably that from this equation, now we derive two further equations. One is that pressure is equal to minus partial derivative of A with respect to volume at constant temperature. This is one definition and the second derivation is partial derivative of A with respect to temperature at constant volume is minus s. And then if I start with G, G is equal to h minus T s.  Extend it further.  No problem.  You have T d s cancelling with T d s, P d v cancelling with P d v. So, I have d G is equal to V d p minus s d t. So, therefore pressure derivative of Gibbs function at constant temperature is volume and temperature derivative of Gibbs function at constant pressure is minus s. As you will notice that such equations allow you to obtain pure thermodynamic definitions of some quantities, thermodynamic quantities in terms of different derivatives. For example, look at here the entropy can be defined as temperature derivative of Helmholtz function at constant volume and at the same time entropy can also be defined as temperature derivative of Gibbs function at constant pressure. So, therefore, when we have expressions connecting Helmholtz function and expressions connecting Gibbs function with canonical partition function then what we have is then we can also obtain entropy volume and some other thermodynamic quantities in terms of canonical partition function through such correlations ok. Now, if we selectively consider only gas let us say we selectively choose only gases four gases P v is equal to N R T when I write P v is equal to N R T that means I am assuming that the gas under consideration is an ideal gas. So, therefore, if I choose to work with ideal gas and consider this equation a minus a 0 is minus k T log q and I substitute minus k T log q and then I have plus N R T in place of P v I am using N R T and further if I choose to work with monatomic perfect gas then as we have been discussing recently that we need not consider rotational and vibrational contributions and for as the sake of discussion we can also exclude electronic contributions under normal conditions of temperature and secondly indistinguishable molecules indistinguishable molecules or atoms. That means I will write q is equal to q raise to the power N over N factorial these we need to now consider. So, therefore, for discussion ahead I will choose this equation and then use q is equal to q raise to the power N by N factorial and then proceed further. Let us carry it forward that is g minus g 0 is equal to minus k T log q plus N R T minus k T log q plus N R T and we will use q is equal to q raise to the power N over N factorial indistinguishable molecules ok. Let us proceed g minus g 0 is equal to minus k T log q raise to the power N over N factorial plus N R T.  So, therefore, I have g minus g 0 is equal to minus N R T log q plus N R T log N I will take minus N R T as common and once you take that as common you have this expression g minus g 0 is equal to minus N R T log q by N it is worth noticing here that we started with Gibbs function in terms of canonical partition function and when we end up it connecting with the molecular partition function what we have in the expressions is number of moles gas constant temperature molecular partition function and the total number of molecules atoms or particles. Now, remember that this is the molecular partition function and since we have decided to initially apply it to monatomic perfect gas therefore, this molecular partition function is equal to the translational contribution to the partition function all right this obtained equation into another how is that. So, I have g let me write g by N minus g by N g 0 by N is equal to minus R T log q over N into N A what I have done is I have divided both the sides by the number of moles and I have converted the total number of particles or total number of molecules as number of moles into Avogadro constant. So, g by N is the molar Gibbs function minus molar Gibbs function at absolute 0 minus is equal to minus R T log q M by Avogadro constant. Right it is much easier if we deal with the molar properties because then we do not need to worry about the size of the system. So, therefore, the equation which connects the molar Gibbs function with molar partition function is g M minus g M naught or g M 0 is equal to minus R T log q M by N A ok. If you want you can leave in terms of the actual size of the Gibbs function and as I said sometimes it becomes very helpful when you compare the molar properties and then you divide by N you can discuss in terms of the molar Gibbs function all right. So, what we have is now g M molar Gibbs function is molar Gibbs function g M minus g M 0 is equal to minus R T log q M by N A and standard states we have discussed many time what is the standard state substance should be pure temperature can be any pressure has to be 1 bar right. In standard state Gibbs function in standard state molar Gibbs function will be written like this ok pressure is equal to 1 bar temperature any substance in pure form. And if I apply this condition the new equation that I develop now in terms of standard state is g M 0 g M naught minus g M naught at at 0 is equal to minus R T log q M naught by N A. Just note down these differences I have which I have put naught naught naught that means pressure is 1 bar what is the significance of putting this condition of standard state over here is that when I utilize this equation when I use this equations in future to connect with other thermodynamic properties then it becomes g 0 then it becomes easy. For example, it becomes very important to understand the meaning of delta g naught and the meaning of delta g always distinguish between delta g and delta g naught delta g naught is connected to equilibrium constant by minus R T log k. Now you will be able to appreciate that if at a later stage I need to connect g M naught or free energy Gibbs function under standard state conditions with equilibrium constant then I need an expression in terms of g M naught that is the reason we have now express this in terms of standard state. So, that any differences in the value of molar Gibbs function under standard state conditions can be connected with equilibrium constant. So, I hope that the discussion on Gibbs function and its relevance has been useful and here we demonstrate that we can get Gibbs function or molar Gibbs function from the value of molecular partition function that is from spectroscopic observations. Thank you very much.


The number of internally displaced persons in various camps in Burnu state is now estimated to be over one million as a result of sustained armed heltsmen attacks on communities in the state. Governor Samuel Otom made the revelation today while addressing IDPs at Eibam, one of the camps in the state. By calling on donor agencies, philanthropists and humanitarian workers to assist in addressing the plight of the IDPs, Governor Otom said resources of the state had been overstretched, appealing that a government requires support to be able to cater for needs of the affected people. He restated the resolve of his administration not to repeal the open-grossing prohibition and branches establishment law of the state. The agenda was not able to grace. It was to kill, to destroy our homes and occupy the land. That was the original agenda. Now that the law is working very hard, they are after our lifestyle guard, wherever they are and their parents, they go about killing them. But I want to send this message to them. It doesn't matter how long it takes. One day, the God of Justice will visit them.


Hi, I'm Craig Venskis regional sales manager for Benchmark a promo product brand and I am excited to be going to Pack Expo East I'll be there live and in person. So please be sure to stop by booth 2304 and See me in our automated packaging solutions. And when you visit Mention, you saw this video and receive a free gift This message is brought to you by a real salesperson and not a handsome actor portraying one My name is Alan Traber president of the latest and we're really excited about seeing you at Pack Expo East in Philadelphia March 21st to 23rd. Our booth number is 2709 we look forward to seeing you there. We have great equipment and fantastic technologies to share with you in person This is Matt Jones from Doerner manufacturing I'm looking forward to seeing you in Philadelphia, and we're really excited to be exhibiting there And I'm looking forward to getting my cheese steak on Hi, I'm Greg Burgeig vice president of sales and marketing at Pack Machinery Super excited to have you stop by our booth at Pack Expo East where we can discuss ways to help you optimize your Poly bagging vacuum packaging flow wrapping and other types of packaging processes. See you there Hi, I'm Bill Laundrie. We're looking forward to seeing you at Pack Expo East at booth 1206 look for Rena by Quadion. We'll be showing our inkjet color printing systems They can be cool stuff like this and a lot of other things. We'll see you there


Hey traders, this is T Bradley 90 from the my investing club chat. I'm one of the top mentors and moderators in chat as a Special gift to our viewers on YouTube We have created a free two-hour course to help teach you how to start a consistently profitable trading business and Identify high-paying setups in just 30 days. There will be limited seating every week So register for the course and reserve your spot now Using the link in the description as a special bonus for everyone that watches the entire video We will give you the link to a free 10-hour additional mini course that has never been released to the public Register now before all slots completely fill up Yes, probably have a starter here in the risk five cents on this got filled on TV The really tight risk to reward trade and it's super small starters, so Can think about adding over 38 maybe approaching this 40 and consider putting on another piece over 36 Right I Can move the rest of 32. Why not? That might be a little tight that might be a little tight on the one night. We'll see Got filled on TV. All right, so I added there going for this Going for this 40 to 45 break and Out of tight risk a little wash for a recycle Got filled on TV. All right got the recycle So now I should probably take this recycle off right here at the high of the day because that that's being Um Respectful to the high of day And if we start to play the are we gonna hold 235 to 240 like we start playing around as 240 as a top I'll probably just exit this train Because you know that's gonna that's gonna be pretty weak after a high of a break So I'm hoping for some emotion into that 280 level You know there I gotta sell right up there in 70s But you know, it's natural to stop a little bit short of resistance So this is where I feel there's a fundamental reason if I start to start feeling impatient and that we're stalling too much You know, there's a good reason maybe for now for me to start to Think about taking profits a little sooner because we're getting into this 280 level and you know Psychologically longs aren't gonna want to buy there and shorts aren't gonna want to cover there So if we start to stall too much, I'm gonna start taking it off And so now I've recognized there's a fundamental reason now where I can You know why I might be getting impatient and I've identified it It's like hey people are approaching 280 and now my gut feeling to you know Get a little greedy on the cells and take it off a little early. There might be some warrants to that right But before I was strictly just being impatient and I thought and I figured that out too And that's why I wanted to talk through it and sometimes talking through it can help Let's see. Can we get up past 70? I think we can Yeah, we're starting to see that stall like everyone knows 80s survive who wants to buy in the 70s, right?  We're close. I'm right above 70s Hey traders, this is tosh. I go by t bradley 90 in the my investing club chat Just wanted to reach out and say if you have any questions about m. I see joining m. I see maybe you're a member already You have three ways to contact myself personally and through m. I see you can hit our social media You can hit me through pms in chat or you can contact us through my email at tosh at my investing club.com That's tosh at my investing club.com. I will get back to you in a timely manner And I'm saying this because I'm here to help and I don't want anybody to be afraid to reach out and ask Any question that they have we are here for you guys. All right. See you guys


the great search brought to you by Digikeynator. Thanks, Digikey. This is the time of the week where LadyAida uses her power of engineering to help you find the things you want to find on digikey.com. What are you looking for this week, LadyAida? Okay, so this week chip shortage is not quite ending. It's relaxing a little bit, but there's still a lot of parts that didn't make it to the other side. And one of those is the fan 5331. Now you might be saying, LadyAida, you covered the fan 5331 a couple months ago. I remember that you found an alternative for it. No, no, no. My friend, that was the fan 5333, which is the constant current version of this boost converter. I'm now going to be looking at the constant voltage output version of this boost converter. The boost converter before was what I used for LED backlights on four, seven, ten inch TFT displays. It's one, you know, big LED chains where you want to have a constant current of 20 milliamps through multiple chains of LEDs. The fan 5331 is what I use often times for e-ink and OLED and TFT displays where I need a bias voltage, especially for OLEDs. This is very common. You need to give it a 9, 12, 16 volt bias to activate the OLED even though it's not like the main power source. You do need, you know, 50 milliamps or so, maybe 20 to 50 milliamps available for all sorts of devices. As I just mentioned, sometimes audio circuitry also, you'll need plus 12 volts even if you're not using a full 12 volts for your audio signal. The rails need to be hired because you need a headroom for your audio amplifiers and they go up to maybe six volts. So again, you know, for biasing, this isn't a power. Well, that's not what I would call a power boost converter. Although if you only need 100 milliamps, then it'll do the job as well. So let's go to the computer and let's look at this chip. So the fan 5331, I really, really love this boost converter. 1.6 megahertz frequency, adjustable up to 20 volts and it has a built-in one amp peak current switch and it comes in a SOP 235. This thing is like, it was a bread and butter. Like I could toss it to any circuit. It was, you know, all about a buck or less. It did the job beautifully, perfectly. They never blew up. They were super stable, low shutdown current, low RDS on, lovely, lovely chip.  That's a great question. If you were to find this part on Digikey, you would see it is last time buy. Last time buy means they will do one more run. And then, you know, if you need a couple of years worth, please put in a couple of years worth that you need to complete your manufacturing until you can change over to another part. I will do a last time buy because I, you know, I like to have some backup for, yeah, sometimes you find alternative and the alternative isn't quite perfect. You might as well put in that last time buy order. However, I've also learned sometimes last time buy means no, that's a, we actually are never going to send it to you. I'm looking at you STMP 811, who's last time by lasted two years, and then I never actually got the part. And then they told me they will never send it to me. So it does happen. Not say it's going to happen here, but I've learned when I see last time buy, I find alternative immediately. So a couple alternatives suggested, but actually, I wanted to, you know, some of these might be okay, but let's use our patented search ability to find something similar-ness. So we want a DC-DC regulator with internal switches and one output. I'm not as picky about the internal, you know, the Minimax input voltages, because again, it can be wider, it can be narrower, basically as long as it's three to five volts. I'll try to find something with about 20 volts, one amp switch, and hopefully high frequency. I do want it in SOT 23.5. I want it ideally to be pin compatible and functionally compatible, so I don't have to redesign. Okay. So, and then, you know, we're going to get pricing at 1,000 pieces. So this is fun. This is the, you know, this image is not correct, because this is SOT 23.5, but it's good to know. And there's a couple obsolete parts. Here's that fan 5331.  And then a couple others in that family, you can see the fan 5333 is also last time buy. So let's, let's have a look at active, and that'll cut it down like half. So only 30 options now. I also want to look for normally stocking only, because as some of these are, you know, not, you're not available. I don't mind if it's marketplace, that's okay. One thing I'll note is a few of these are step down. They're not boost converters. Like this one, this is a regulator, and this is a regulator, and they're step down converters, not step up converters. So we do want to note that, you know, you want to make sure you pick both SEPIC style and step up. SEPIC is a single-ended, something-something converter.  Sometimes you can configure, you know, by adding more trends, yeah, more shocky diodes and more inductors, you can kind of reconfigure it. So it's okay for the voltage goes a little bit under or above. That's okay. We'll just select both. The voltage supply max is fine. The voltage supply min, all these are fine. They all cover three to five volts. That's fine. And the voltage outputs are, for these are also fine, because they just want at least 20 volts. The current output per channel, again, this is confusing because there's output and switch. Usually they're specced by the switch, I will say. So that said, if you look at the switch current, you're not going to get, you know, there is one that's 2.8 amps and it's like, wow, that's cool. But it's out of stock. It's the LM3410. Currently not in stock. So that's a little sad. Maybe I'll actually say only one will get in stock ones as well. Okay, so back here. So the current output channel, so, you know, basically there's 550 milliamps. That's kind of the max. So if that current output is important to me, the LM2704F, it's a little bit more expensive. It's $1.25 on tape and reel. But, you know, it does do the job. It's adjustable up to 20 volts. You know, built-in switches, half as much, 550 milliamps. Great for LCD bias supplies. What a coincidence. And then, you know, this is basically your classic circuit, which is the same circuit you'd use for the FEN 5331. And I did check the pinout. The pinout is identical. I can quickly look it up to verify for you. So it's switch, ground, feedback, shutdown, be in. And this is switch, ground, feedback, shutdown, be in. So one, two, three, four, five. It's in the same order and the same circuit. Although the feedback resistors may have to be adjusted, but that's not a big deal. But otherwise, this looks, you know, very similar. You have to give it the shocky diode and the inductor and does the rest. So this one's good. However, you know, for a lot of the bias circuits, I don't need necessarily 558 milliamps. I'm glad it's available. And then, of course, if I'm willing to spend even more, there is a version that has a built-in 2.8 amp switch. So that's good to know. And it's actually kind of nice. It's also 1.6 megahertz. Again, it's more expensive. The original FEN 5331 was about 75 cents. This is $1.50. But there is something available, the LM3410. So that's good to know. But for my purposes, I'm actually kind of OK with using, you know, 350 milliamp switch. So again, I only need like 10, maybe 20 milliamps at 9 to 12 volts. It's not huge. Again, it's not a power converter. It's a bias generator. So I'm actually OK with this one, the LM2703. Right?  But this one does the job. And hey, it's in stock, hard to beat. But this will do the job quite well. Again, 2.2 to 7 volts in, up to 21 volts output. Simple boost converter. It'll do the job and then pin compatible. So I can just drop it in. And for almost all of my OLED biasing needs, this chip will work quite well. And that's a great search.


What is up everybody? Welcome back to the channel you guys. I just want to share this real quick with you just again day in the life Documenting what I'm doing as I'm building my business and This is just a huge huge You know benefit to being able to reach out to Facebook and get your questions answered because Before I remember jumping into Facebook ads and and the support was very minimal like it was hard to get in touch with Facebook You'd have to have like some type of you know mentor that's already crushing it with Facebook ads that you can reach out to which Normally you have to pay some expensive coach to have someone like that by your side, but Nowadays, it's super easy. It's super easy to get in touch with them It's super easy to have have them resolve your issue whatever may be going on in your ads manager and And I'm super grateful for it man. I'm super grateful for it. So what I want to show you is just some simple a simple like Just hiccup that I was experiencing here in the last Pretty much in the last 24 hours. I Installed a pixel. Here's a page that I'm working on right now for a client I installed the pixel and I know that I installed it Correctly because I have the Facebook pixel helper and and it shows me right here And if you don't know about the Facebook pixel helper You definitely want to Google this installed this because this allows you to really test your pages and make sure that your pixel Is installed correctly Go ahead and Google that Facebook pixel helper and then and also Don't mind the little baby that I found laying on the floor back there Don't mind him. He's just chilling learning Facebook ads himself, but This is what you want to install for sure, right? So Facebook pixel helper Install this it's it's this plug-in that will sit up here at the top and and right now as I'm on this page This page has no pixel, you know tracking me as I'm on this page. I can click on it and it will tell me Okay, yeah, I have a pixel, you know tracking and this applies for any website So when you're on any website on the internet, this thing will light up if that website is tracking you with the Facebook pixel Okay, and I never care about who's tracking me. It doesn't even matter. It all that's for advertising purposes, you know Really, so I don't I don't care about anyone, you know having their pixel and and and they're tracking my activity It doesn't matter at all But I use it for for my purposes right to really make sure That I have my pixel installed correctly. So I've installed a pixel on pages a million times And and and you know it clearly shows right here that it was installed correctly But when I was in the ads manager And I was I was creating these custom audiences and I was doing this yesterday When I come over here And I look at my custom audiences over here in the availability it was showing inactive It was showing inactive on the seller guide leads page. These are my custom audiences I have a custom audience for everyone who lands on the page and does not opt-in I have a custom audience for everyone who actually opts in Right, and then I have obviously a custom audience for for video views for people that are watching the videos But just on the pages alone. That's where your pixel has to go your pixel has to go on the pages So I created these I installed the pixel on these two Specific pages and then I created a custom audience Around these two pages, but for some reason it was showing inactive. It wasn't showing green It was the the the dot was gray and it was showing inactive It was reading inactive on both of these audiences and I'm like dude Why like why is it inactive when the pixel is installed correctly? and then also when I came over here to I click on the dots and I go to events manager This is where it was also showing Not it wasn't showing inactive But it was it was showing it it was showing that the pixel hasn't been installed yet, and I'm like wait a minute Yes, it has been so what I did is I Let's see what it says over here now because it's the first time I'm coming back to it. Okay, perfect. So we're so So we're good. See so right there active. Okay, we're good So prior it was showing just a few minutes ago It was showing pixel not installed yet, and I'm like dude. Yes, I'm like it I installed it yesterday Like why is it still saying that so I'm like dang dude I got to find out what's going on so I reach out to Facebook and that's the whole purpose of this video This is how you want to reach out to Facebook. So you come over here. You click on this question mark Right here, and then it's gonna bring up, you know Some different articles and different things that may apply or may relate to your your your question And what I did is I just simply came down here, and I clicked on help center and That brought me over to this part over here, which is the faith the Facebook business help center Okay, and what I did over here is I simply came down here, and I found I Went to let me see I went down to I went down I think I clicked on and this was just a few minutes ago. Actually, no, I clicked on support right here So I clicked on support and then and then obviously there's a ton of topics There's a ton of articles that that you know they put down that are that are very informative, right?  I've done this a million times. Why is the pixel not active, right? And there and I just truly believe there's no article that's gonna tell me why like I installed it correctly It should be active bottom line. So I'm like, okay I don't want to read any of this so I scroll down and right here Facebook business help center find answers or contact support I clicked on get started and then it showed me right here How can we help and whatever you're you know, you're you're asking about I clicked on ads and Then I went down to chat with the representative right there you guys that right there You click on that and then it opened up, you know in the in the in the in the in the Facebook messenger And this was the conversation that I just had With with my boy John. So 835 just a few minutes ago And I mean I'm actually logged into a client's account So I was chatting with John as I was Jill, you know what I mean, but no one cares He doesn't know and no one cares at all so he took me through literally I spent maybe 10 minutes and and to tell you the truth. There was really nothing he did He because because we ended up we ended up resolving the issue, you know before he was able to put in a full, you know bug report us a full, you know Like investigation on the issue For some reason all of a sudden it started showing active and I'm like dude, how did that happen? You know, let me go back to it We'll go down to audiences So again, the first two audiences were showing inactive and so as as I'm messaging him I'm like John look what's going on man. Look, I installed the pixel correctly like I even show it You know, it even says here in the in the Facebook pixel helper because it's what he asked me I'll do do you have an ad blocker? Do you have the Facebook pixel helper installed? Like can you make sure that it is it's installed correctly and so I'm sending him screenshots of everything, right? And that's all it is man I'm explaining it in text and then I'm sending him screenshots of what's going on, right? There's my Facebook pixel helper screenshot. There's another screenshot. I'm showing him how it's inactive Actually, this one was the active one. Let me show you The other one that I sent him So I sent him one up here Because it was showing inactive This one, right? Yeah see so as I clicked on The the audit the event manager it was saying this your pixel hasn't received any activity continue pixel setup I'm like do wait a minute. It should it should have received activity I installed it correctly like why is it is it is it is it taking me to this part and then I also sent him this next one Which is what I showed you guys So this is what it was reading so pixel not installed and again, it's been over. It's been about 24 hours Since I installed it. I'm like dude Why is it still showing that a day later and so that pixel not installed pixel not installed now over here It's showing ready Ready and I'm like John like I don't know what you did bro like I even asked him I'm like did you do something on your end to all of a sudden make it ready and he's all no Do I didn't I'm like that's kind of weird like why did it take so long, you know To be ready and so he he really didn't have an answer for that but But my whole point of this video is to show you guys how to get in touch with Facebook Like that's what you want to do is it's simply go through that process right there Get them in a messenger and just and just be cool with these people because all these people are super cool They're all and that's the weird thing. They're actually really cool Like they I wonder if freakin Zuckerberg, you know trains them that way or whoever the hell trains them right to really be cool Like they talk normal. They they they're very nice like they're very supportive and and and and you want to be that way as well And so you simply just type out whatever the hell is going on and send screenshots To to show, you know, what's going on and and they'll get down to the bottom of it So thank God, you know, this pixel is working now I can start this next ad for this client and Continue to crush it. So that's how you do it You guys get in touch with Facebook through the help center and get your issues resolved All right, I'll see you guys on the next video over now


There's something about carving out a specific time in your day where you say this time belongs to the Lord and I'm not giving it to anybody else. And you have to stubbornly refuse, write that in the comment section. Stubbornly refuse to give that time to anyone else. It's not for your spouse, it's not for your children, it's not for your friends, it's not for your work, it's not for your scholastic studies. There must be a time carved out of every day that is totally devoted to the Lord Himself. This could be time in the Word, time in worship, but of course, time in prayer.


Hi and welcome to the session. Let's work out the following question. The question says given below is the expenditure of a person on different items out of his salary of rupees 14,400. Now this is a table given to us. In this first column we have item that is clothing, food, rent, education and others. And second column we have the expenditure. For clothing we have 2,800. For food we have 3,600 and so on. And this grand total is 14,400. Now we have to draw a pie chart to depict the above data. So let us start with the solution to this question. First of all we see that on clothing the person is spending 2,800 rupees. Therefore the central angle will be 2,800 rupees out of 14,400 multiplied by 360 degree that is equal to 70 degree. Now second on food the person spends 3,600 rupees. Therefore central angle will be 3,600 out of 14,400 multiplied by 360 degree that is equal to 90 degree. Now for rent the central angle will be 3,600 divided by 14,400 multiplied by 360 that is equal to 90 degree. Central angle for education will be 1,800 divided by 14,400 multiplied by 360 degree that is equal to 45 degree. For others it will be 2,600 divided by 14,400 multiplied by 360 degree is equal to 65 degree. So the required pie chart will be this wherein the share of food is from central angle is 90 degree, rent is 90 degree, clothing 70 degree, others 65 degree and education 45 degree. So this is our solution to this question. I hope that you understood the solution and enjoyed the session. Have a good day.


So this talk is just one of the more interesting talks, I think, personally speaking. I'm looking forward to and it's special for another reason because this is one of the few talks which has two speakers who have proposed a talk out of which Padmaja will be speaking today and she's currently working as a software developer at VMware. She's given a lot of talks before as well at Picon US 2017-2018 and at Picon India 2016. She is currently working on a product that enhances customer serviceability by providing proactive recommendations. It's a lot of words but I'm sure she'll elaborate at some point. And she's a data science enthusiast with a strong passion for dance and loves going on adventurous trips. Nice to meet you Padmaja. The second speaker is Bhargava and he's spent the last 17 years helping businesses both large and small use data algorithms to build a moat. He's worked on large scale machine learning problems in transportation, banking, software and networking products. His previous startup was incubated by SAP. Currently he's working at Benize which he co-founded and he's focused on helping small and medium sized e-commerce companies improve conversion. He's presented a talk and workshop in SAP USA, SAP India and Picon India in the past and he's also a good friend. So I'm very happy to be part of this stage and see how the talk will go on, which I haven't mentioned the title of. The talk is let's build a no code tool for small businesses to reduce churn. So I think we are at the 550 mark and Padmaja, the stage is yours. Very good evening to all. I'm really excited to be a part of this year's Picon India edition. I'm sure it's going to be one of the most adventurous version of Picon till date. So disclaimer notice, please excuse me if there are any technical glitches during the presentation. We hope there aren't any. So with that said, today we'll be looking into one of the most interesting topics called as churn analysis. And how in the next 20 minutes you can build an end to end tool which can be used by anyone to perform churn analysis. So before I start talking all nerdy, here is a small introduction about us. So I'm Padmaja Bhagwat, a huge data science enthusiast and a software developer at VMware. So here I work for a team that enhances the customer service ability by providing proactive alerts and recommendations to our customers. And Bhagwat here is a deep learning engineer. He has been early data scientist at many top notch companies and currently he is a founder and CTO at Binaz. And to be honest, he is one of the biggest inspiration for me to be in the stream of data science. So enough about us. So let's get directly started with the talk. So this is how the outline of the talk is going to look like. We'll start off with providing the business context behind this problem. We'll also look into the different steps that are being followed to perform churn analysis. Then we'll look into the architecture of the tool that we're building today. And finally, if everything goes as expected, I'll promise you a very awesome demo towards the end of it. So let's get started. So we have seen that COVID-19 has had a huge negative impact on the businesses, especially on the small scale businesses. And most of them have now moved online. And at this point of time, it is extremely important for these businesses to ensure that most of their customers are sticking with their product for as long as possible. So in this highly competitive online world, businesses cannot settle for reactive approach where they first wait for the customer to abandon their product, and only then they start taking some actions. It is high time we start taking some proactive actions where we perform everything that we can in order to retain the customers for as long as possible. So before we dive into the exact steps that are being followed to perform churn analysis, let's zoom out a little bit and see how exactly the customer engagement lifecycle looks like. So it starts off with you advertising your product, thereby increasing the awareness of the product among the potential customers. Then those potential customers, they start engaging with the product. They start exploring the features. They really like the features that you're providing. So they even get converted into paid customers. Now you expect those customers to remain loyal to your product for the rest of their lives. Now this is what you ideally expect to happen, but real world is never ideal, right? So that's why there are different phases where your customers might start disengaging from your product. And the first kind of disengagement is called as customer abandonment. So in this case, the customer is really impressed with the advertisement that you have put out. So they come and they explore the different features that you're providing, but after that point, they never really come back. So once, after this kind of disengagement, there's yet another kind of disengagement called as customer attrition. So here, the customers seem to be really interested in your product. Therefore, they even sign up for the free trial version. But after that trial period gets over, they never really come back. Now again, this is called as customer attrition. And the third and the worst kind of customer disengagement is called as job. So in this case, the customer is the customer whom you thought was loyal, the customer who was using your product for many, many years, all of a sudden stopped using the product one day. Now this has a huge negative impact on the business because you would have already invested so much of your time and energy trying to nurture this customer, trying to get this customer onboarded for as long as possible. But if the stock using your product all of a sudden, it has a huge negative impact on the business. And this is what we will be focusing on in today's talk, how we can avoid this exact same situation. Because we all can agree that it is much less expensive to retain existing customers than to acquire new ones. So the tool that we will be building today helps us identify this exact phase where the customer, the active customer transitions from being active to being at risk of churning the system forever. So our product will help you understand the exact timeframe when this transition is happening. So since the beginning of the talk, I've been telling that it's extremely important to perform churn analysis. So now that we have established that it's important to perform timely churn analysis, let's look into the exact steps that are being followed in order to perform the churn analysis. So the first and the obvious step is that you have to pre-process your data. You have to convert it into the format that your machines can understand. Then we'll be discussing various different models that can be used in order to perform churn analysis and how you can derive predictions out of the model that you have built. And finally, we'll be building a super cool web application to visualize the entire analysis that we have done in the previous three steps. So for this presentation, we have used an openly available data site called as telecom churn, which you can easily download from Kaggle. So here, I have just picked a few features, but in reality, the data has a lot more features to it. Let me tell you, you can easily extend the steps that I will be talking in the next slide to any kind of data as long as you ensure that your data has these three features. First is you need to ensure that your data has customer ID, which is the unique identifier for your customer. Then you need to ensure that the data has this churn column, which says whether the customer has churned or not, which is obvious because you are doing churn analysis and we need to have this column for sure. And finally, the most important feature that you need to ensure that ensure is this tenure. Now, this tenure period means slightly different for different people. For the customers who have already churned, let's say for this third customer, this tenure period of two months indicate that the customer has used the product only for two months. So the entire lifetime of the customer with the product was just two months. But whereas for the customer who has not yet churned, this tenure period of 34 indicates that the customer has been using the product from past 34 months and will continue using the product in the future. So there's a subtle difference between these two, but I think it's really important to understand in order to do the correct kind of prediction. So as long as you ensure that these three features are there, remaining all features can be anything depending on the kind of business you are into. So again, depending on the type of data, you can perform different kind of preprocessing steps on it. In this case, as you can see, most of the features are categorical. So we'll be going with the simple one-hot encoding. And find us provides this very handy function called as pd.getDummies, where you just have to send all the categorical features and boom, it creates the entire column of one-hot encoded features. So again, if your data contained time series data, which talked about the way your customer purchased with your product, you can probably use this TSFresh package, which will help you create the features out of your time series data. Now, again, depending on your data, you go ahead with different kind of preprocessing. In this case, we are sticking to a very basic kind of preprocessing, which is creating one-hot encoding out of the categorical data. So once we have converted the data into the format that can be understood by the model, let's explore the different ways that we can use to build the model. So by looking at the data, you think that this is a straightforward classification task. So you can think that I can use a simple decision tree or logistic regression to perform this churn classification, which is great. These models will tell you whether the customer is going to churn or not, and will also give you the probability with which the customer is going to churn. But all that you are looking for in here is, you're trying to build a model, which can tell you at what exact point of time the customer is going to churn, because you want to take the actions at the correct point of time. And that's when the survival analysis models come into picture. So there are different kinds of survival analysis models, but for this presentation, we will be sticking to the Cox Proportional Hazard model, which is the most popular one in the survival analysis model. So again, Python provides this very useful package called as LifeLanes, where you can play around with different kinds of survival analysis models. So as I told before, you can see in this plot, on the x-axis you have tenure period, and on the y-axis you have the survival chances of the customer. So you can see that the survival chances of 1 indicates that the customer has lapping the product and will stick with the product for a very long time. Whereas the survival chances of 0 indicates that the customer is going to churn for sure. So in between these two periods, from the time the survival chances of the customer reduces from 1 to 0, you need to take some action. You need to send some offer to something so that you can increase the lifetime of the customer with your product. So this is exactly why we are going with survival analysis models. It tells you the exact time when the specific event is going to happen. So let's see how exactly we can build this using Python. Although the concept might look a little complicated, you can see how easy it is to build this model using Python. So all you have to do is you have to import Coxfitter from this very famous lifelines package. I highly recommend you to go ahead and use this package. So once you have imported the model, you just have to split your data into training and testing, and you have to initialize the model. And you just have to do model.fit and you have to send the training data as the first parameter and then the duration column. In our case, it's 10-year as the second parameter. And finally, the event column, which in our case is whether the customer is going to churn or not. So you just have to follow these three simple line of code in order to build your churn analysis model. So it is as simple as that. So after you have built this model, if you do model.plot, it will exactly tell you how important each feature in your dataset is. So on the X-axis, you can see the hazard ratio. Just think of it as some coefficient, all right? And on the Y-axis, you can see the exact features that are being used to train the model. So all you have to remember is, hire the hazard ratio, hire the chances of customer churning out, which is not what we want. We want the exact opposite. We want our customers to stick with the product for a very long time. That's why we focus on the features that has the lesser hazard ratio, right? In our case, these are the last four features has a very low hazard ratio. So now let's just pick one of the features, which is total charges, and see how changing this feature impacts the survival chances of our customer. So you can see the total charges has decent hazard ratio of zero. So now let's see how it impacts the survival chances, right? So all you have to do is, you have to do model.plot partial effects on outcome and just send the feature that you're interested to learn about. So here you can see the black dotted line indicates the baseline survival curve of the dataset. Now by some chance, if you just reduce the total charges in the dataset to zero, you can see the survival curve has moved towards the left, which means the chances of customer surviving is dropping down rapidly and it is dropping right from the 10th month itself. Whereas if you increase the total charges to 4,000, you can see that the customer is sticking with the product for a very long time, right? Only after 60th month, this chances start reducing. So which is obvious, right? If the customer is spending too much, if the customer is spending a lot on your system, then it is obvious that the customer is going to stick with the product for a very long period of time. That is what this graph is telling us. So now that we have built a model and we have seen how each feature impacts the survival chances, let's do the exact prediction. We need to know at what exact point of time a given customer is going to churn out so that we can take a relevant action before that, right? So for that, we will be looking at only those customers who have not yet churned. The customers who have already churned, you cannot really do anything about that. So for the customers who have not yet churned, they are called a censored subject. So all you have to do is you just have to do model.predictSurvival function and send the censored subject as an input. That is the entire prediction of when the customer is going to churn. So this is how the graph looks like. The dotted line, what it indicates is the survival chances of this specific customer and how it is varying over the period of time. You can see at 40th month, the customer will definitely churn out. But there is a slight issue with this prediction that the model has given. The model thinks that the tenure period of 22 months is the total lifetime of this customer with the product. Which is not true. As I had mentioned before, for the customers who have not yet churned, this just, tenure period just indicates that the customer has been using the product from past 22 months and will continue using the product. Therefore, till 22nd month, you are for sure you know that the customer has been sticking to the product, right? Therefore, you have to condition your prediction by dividing each one of the value with the tenure period. So now you get this bold line. Here you can see that till 22nd month, the survival chance of customer is extremely high, which is one. Only after that, it starts reducing. All right? So here we have seen how the survival curve of the customer is varying over different period of time. Now if you want to take some action, let's say you would want to send some offer when the survival chance of the customer reduces by 50%, then Python provides this very simple function again called as queued survival times. So using this queued survival times from the lifelines package, all you have to do is you have to send a percentile and you have to send a conditioned graph that we got in the previous plot as an input. And there you go. You will get the exact month when the survival chances of this customer reduces by 50%. So you can see that at 30th month, the survival chance of the customer has reduced to 50%. And you can see the remaining charges, obviously 22 minus 30, multiplied by 89, which is around 712. So we know that we have roughly 8 months to save this customer, right? So we know that at 30th month, we would want to send some offers. Now those offers cannot be some random offer. It has to be very much relevant and targeted to the audience. That's why we again come back to the feature importance plot that we saw in the beginning. So as I had mentioned before, we will be focusing on those features which has less hazard ratio. In this case, it is payment by credit card, payment by bank transfer, whether the customer has one year contract or two year contract. If the customer has either one of these four features, there's a high probability that the customer will use your product for a very long period of time. Now instead of just talking, let's exactly see how each one of these features impact the survival chances. So again, going back to this customer, you can see the original subscription of this customer looked something like this. The customer had only subscribed for credit card payment and had no other subscription. So if you're sending some offer, make sure that the customer subscribes to this two year contract. So from this graph, you can clearly see that just by getting the customer subscribed to this two year contract, the survival chances like more than doubles. From 22, it is now as high as 55 month. So similarly for other features as well. And also you can see that if customer unsubscribes from this credit card due to some reason, the survival chances drops. So you don't want that to happen. So till now we saw how to pre-process the data, how we can build a model and how to send a targeted offer to our customer, right? So you are really happy with this. Now you do the entire analysis. Now you go ahead and present this to your boss. Now if your presentation looks something like this, all they are to think is what on the earth is going on, right? Because this is not at all comprehensive. So your presentation has to be such that everyone, no matter what their background is, should be able to identify what is going on. They should be able to tell, okay at this exact point of time, the customer is going to turn up, right? So that's when you start thinking, okay, fine. What if I build a web application out of it? Then you start thinking, okay, I need to start learning all this web framework such as Django or Flask, and then you start thinking about learning UI frameworks such as different UI frameworks, right? So what if I tell you, you don't have to learn any of those. You can build an entire end-to-end web application just using Python. So if you don't believe me, so there is this very cool package in Python called as Streamlit. It is the easiest and fastest way to build a web application using Python. And the best part is you don't even have to know any HTML and CSS for it. So if you don't believe me, you can see how simple writing the Streamlit code is. So all you have to do is import Streamlit as ST. And you have to keep embedding these Streamlit statements wherever you think it's necessary into your Python code itself. You don't have to create anything separately for this. For example, if you're doing a matplotlib, all you have to do is st.pyplot and you send the figure that you have built using matplotlib and that goes on to your web application. And if you think the plot needs some explanation, all you have to do is you have to do st.write and send any kind of description that you think should go on the website. It is as simple as that. And running the application is even more simple.  You have a very nice web application running on your local server. Right? So in order to make this web application publicly available for anyone to use on the real-time basis, obviously you have to deploy this on cloud. In our case, we have deployed it on Heroku. So you can just follow these four simple steps to deploy any Python applications on Heroku. So for that, you just have to ensure these two files are present in your project. First is the requirement.txt, which has the names of all the packages that are required to run the Streamlit application. And you must have this proc file. So this proc file contains the command to run the Streamlit application. So in our case, it is just Streamlit run and the main Python file name. So as long as you have this, you are good to deploy your entire application on cloud. So this is what the architecture of today's demo is going to look like. We are going to feed in the CSV file as an input and we are going to build our model using all these super cool packages that we just spoke about. And then we'll be using Streamlit to build our web application. So let's directly jump into our demo. Yes. So yeah, this is the final web application that was built. And you can, from here, we'll be selecting our input file. So you can see how nicely it presents the entire information on the website. So this is the raw data that our website, that our database contains. And this is the pre-processed data. And then let's go ahead and build the model. So this is the different survival curve, how the survival chances varies with varying total charges. And this was entirely built using the Cox proportional hazard model. You can read more about that here. And then we can see how the model predicts. You can select any customer from this top term for which you want to predict the exact time when this customer might turn. So let's keep the default selection itself. So we can see that for this customer, at around 60th month, the customer is going to turn. And till around 35, 35th month, the survival chances of customer is completely high. So we can see here that at around 49th month, the survival chances of this customer drops by 50%. We can roughly see that from the graph as well. At around 49th month, it is dropping to around 50%. Now if you think that you cannot wait till the survival chances reduces to 50%, if you want to take action in the very beginning, then you just have to increase the criticality. Okay, just a second. We selected this data, we built the model. And this is the very nice feature, importance graph that we saw. And we are making up predictions. So if you increase the criticality of, you will see the exact time. In this case, we have increased it to 0.7. So here we will see the exact month when the customer is to 70%. Okay, it just takes a while to run. So yeah, it is coming slowly. Okay, at around 44th month, you can see the survival chances of customer has reduced to 70%. And finally you can see how changing each feature impacts the survival chances of your customer. Okay, there is some issue. But if you look at the model diagnostics, ultimately you need to ensure that whatever data, whatever model that you have built is good enough for any kind of prediction. And here you can see that the, our model is predicting pretty good for the lesser tenure period. And for the higher tenure period, our model is not really able to capture the entire essence of it, which is fine to some extent because you would want your model to perform really well when the tendency of the customer to churn is high, which is in the beginning of the, beginning stage of the customer lifecycle, right? So this is the entire application that I've built within just like a day. I'm sure you can do the great job with all your design skills and all. So if I can build this within a day, definitely you can do it too. So this is the entire summary of the talk. We pre-processed the data using pandas and if you have distributed data, go ahead and use tasks. We predicted the churn using left lines package and then we built a web application using streamlet and we finally deployed all our changes to the local. If you're really interested in playing around with this model, you can find the entire code in here. So these are the references if you are interested to learn more about this topic. And that's pretty much about all about it. Thank you so much for attending this talk. We are now open to taking questions. Thank you for awesome talk, Pramaja. And I appreciate that, you know, we kept it within time and also more from a topical perspective, a lot of people will appreciate that it is, it doesn't actually require a lot of code to go the last mile, right? Because that is what people, they do all the fancy stuff, but then they struggle at the end how to deploy, how to... Exactly. Exactly. We're open to questions. Yeah, so that was the whole idea of this talk to make sure that you not only build an amazing product, but you also present it in the most amazing way possible. And with Streamlet, it is definitely possible to do it without having to learn too many new tools. Right, so there have been some comments during the talk. Right, okay. So one is this looks similar to R Shiny. So do you have any experience with R Shiny? So this is like, so this is like literally, and of course, Shiny works only with R, so this is like one take on how it works, but it makes a lot more usage. Well, obviously it's hard to compare it with Shiny because Shiny has been around for a very long time. Streamlet just came, it's been about for a year, but it's gone the venture route, so there's been a lot more interest in terms of building this and then having more flexibility. But in the Python ecosystem, obviously this is the most popular one. I mean, this is the only one that provides the ease of use. There is a dash as well. So dash is predominantly for dashboarding. So if you think about these two things, if you do dash, dash is literally packaging plotly and then building dashboards, right? But what Streamlet provides us, access to APIs. So if you see this, what we have done is actually build the models and then provide the models as an API. We didn't have to explicitly go and build a flask or a Django app, as Padma just told. We didn't have to do specific stuff, okay, do you know how to do routing? Do you know how to do deployment? All those things have entirely abstracted away to some meaningful extent, right? So that makes it going to production that much more easier and simpler, especially for a data scientist who doesn't have so much of web skills to start with. Right. All right. So Sameer is asking, can you share the GitHub? Padma, can you throw up the resources once more? Yeah, so this is the link from where you can access the entire code. Right. Yeah, and I, for my part, I will get all the resources from Padma and Bhargava and I'll put them up on the Zoolog room and again, they'll all be on Twitter. We'll send out the mail, all of those good stuff. I think we are excellently on time and we also have the next speaker, Jennifer, in line. So Bhargava and Padma, thank you so much. Padma, thank you for an awesome talk. It was very clear. I think it was the pacing was perfect and it was good. Thank you. Thank you. Thanks a lot. I'm going to have you step down from the stage so we can move to the ads and then to... Thank you.