Hey everyone, welcome to this week's video update today's Friday March 20th before we jump into the alerts and the current positions Just want to give a little bit of commentary on the markets overall We've got about a little over an hour left in today's session at the time of this recording S&P's down 50 Dad am 4 plus Nasdaq down over a hundred Russell the strongest of the group still down just under 1% so The the markets are sliding today They actually bounced up earlier in the day or actually last night and came up to about the 2,500 level Which is actually right at the number that I was looking for on my butterfly But then it quickly retraced and and we're going lower at this point so by the end but within the next hour a lot could change but Basically, you know, I still think that we get a pretty sizable bounce higher Sometimes soon now, you know, whether that is early next week next week two weeks. I don't you know, who knows? But I think we will But I but I also don't think we've seen the the lowest of the lows either so What I was anticipating kind of my Hypothesis if you will was that we're gonna get a bounce today and or early next week and then and then roll over But who knows what'll happen. That is just kind of what I'm playing for overall We do have a little bit of long Delta overall in our portfolio. So we would definitely benefit from a little bit of a bounce So that that's kind of what we're thinking here Let's go in let's go. Well before we jump into the alerts. Let's talk about who got caught being hot in the community So Andrew Roan, he's been with us for a few months and just started right off the bat posting Good questions trade ideas trade, you know posting some of his trade experiences both good and bad You know, I love I love, you know, some people only want to post their winners, right? And then some people are very frustrated. They only want to post their losers love love when you guys post both good and bad I think it really helps other people understand a when you learn from your mistakes if you can share that with others, that's always a big deal and then obviously You know posting good trades to that went well or posting before you even even know what the trade outcome was Is is is very helpful as well. So Congrats Andrew keep up the heat and appreciate all the commentary in the community Love having you in our NT family So starting with the alerts Going back to the first of the week, which was the 16th So first was a rolling adjusting trade and IWM So we did we continue to roll down our short Delta verticals and to keep that short Delta in this case You know, we kept some in April and some in May in this case with IWM We stayed in that same cycle with 32 days to expiration. So if we take a look at IWM IW the Russell's been the weaker on this entire slide that the Russell's Definitely been the weakest small caps getting hit the hardest, but here is here's where we're at So price is well inside of our range got some more room for some more downside there So just continuing to hold on to this for that short Delta exposure Next trade rolling adjusting trade in DE kind of a similar situation. This is a This is a short call vertical If you remember if you've been with it with this trade since the beginning it actually started out as a long put vertical By mistake we kind of flipped it over to a short call and we had earnings coming up So we just left it the way it was so it's now a short call vertical But same thing we stayed in the April cycle of 32 days and just rolled down our strikes from 155 160 down to 131 35 and John Deere's been getting hammered Down another almost 4% today So we are at a point where we could roll this again, and if we do so, you know April's got what 28 day? Yeah 28 days So the one thing about John Deere is there's no May monthly options yet So we'll take our time with this one those will come out Eventually and then we'll potentially and then we'll potentially roll out Or depending on where you're at in the cycle if you want to lighten up your short Delta You could also choose to close this out, you know, we're over 50% of max profit But but the way I look at this is You know we always talk about hey, you know close this once you get to over 50% of max But the way the one thing to kind of consider when you're looking at this is look at the slope of the P&L line Obviously the further you get down it starts to really flatten out right, but we've still got a pretty steep equity curve and as we get closer expiration that the gamma will make that even steeper so as long as we got a decent, you know We want this for short Delta. So as long as we got a good profit potential still and a decently steep curve I don't mind keeping on a little past 50% of max profit But that's kind of the the logic once you get past 50 it starts to flatten that a little bit and especially up here when You're about 80% of max profit So we'll keep this on the other thing. We don't you know, we try to we don't want to get whips odd either So if we do get a bounce next week, you know, that's gonna put price way up here So we don't want to roll up and then get the whiplash where it busts out of our range So it's just a managing and massaging game. Of course, we have multiple positions on so we never know what's gonna happen So we just kind of Do them at different expiration cycles roll them on different days And that's why we talk about diversifying those days to expiration diversifying the time that we that we make those adjustments. So That is the plan in DE Next trade rolling adjusting trade in ES. So same situation. This is a long put vertical Just rolling down our strikes in this case we rolled out So we rolled from 32 days out to 60 days to expiration in ES So if we take a look at that one We you know, we've come down a little bit since that roll, but we've we're out in a further duration And so I've been getting a couple questions about well how do you how do you choose whether to stay in the same cycle or to roll out and It's it's really just a matter of what I mentioned before we're diversifying our days to expiration So we just we choose some there's not really a rhyme or reason of why we do one versus the other You know, for example in in John Deere, there is no May option. So we're staying in April in ES There's a lot of different options available as far as expiration cycles. So we went ahead and rolled this one out and then the other thing and just that the other thing to consider is the the P&L Volatility in your shorter duration is going to be a little bit more volatile meaning Smaller price moves in the price are going to affect your P&L Positively or negatively depending on on the direction the further out into duration you go that P&L line does get flatter Right in both directions. So it doesn't hurt you as bad if the market moves up And it doesn't you don't get as much profit as it moves down So those are just kind of the considerations We're looking at when deciding on the time frames and and where to roll those and of course now that April is out of that 30-day range. We're not we wouldn't roll any more inside that April cycle Any any additional rolls will be out to May or a different expiration Next trade opening trade in VXX. So we put on a short call vertical in VXX This one with 31 days to expiration You know VXX is just obviously being on a tear to the upside with volatility Expanding stocks going down. And so we thought it was time to dip our toes into that So if we take a look you can see we're up a little bit in fact earlier today We're quite a bit more but now with stocks falling applied volatility is expanding So we're just up a tiny bit on the trade but If we put our price slice at the break even in fact, let me just do that here 418 to the expiration date click on the chart and click back So we get a smooth line you can see it's got about a 67 and a half percent probability of a success at this point But of course VXX also has that downward drag which In a normal cycle with the contango and backwardation if you understand that the rolling of the futures behind the pricing of this But really what we're what we're playing for is we put this on right here and Took a little bit of heat as it expanded even further and now it's come down and we're a little bit profitable So, you know, we're just playing over the next 30 days that you know price is gonna land somewhere somewhere down here and You know who knows may may not but we're staying small We may add to this if we get another big push higher in VXX But for now we're just gonna hold on and see what happens Next trade rolling just in trading QQQ so roll this one out to the May cycle with 59 and again rolled our strikes down from 201 206 down to 175 180 so here's the cues and And price is hanging out right here. So not too far off from where we made that roll Next trade rolling just in trade and Apple so another kind of same theme here and this one We just kept in April with 31 days just rolled our strikes down So we had we were well over 50% of max profit So just rolled those strikes down in the same cycle pretty close to where we did that So again, just holding this for a little bit more short delta exposure Rolling adjusting trade in SMH. So this is where we had a short strangle and we rolled the calls down So we rolled them from 147 down to 121 and so we were not and we stayed in that same April cycle We're not inverted. So we still got the 117 puts 121 calls and we're just gonna hold onto that until we get closer to 21 days And then we will roll out in time So prices outside of the range But if you look at the untested side the calls you still see we got a decent amount of juice in those We're not looking to roll down the calls again yet, but But when we get down to you know end of next week early the following week We'll be rolling this out from April to May because we'll be down to that around that 21 days to expiration point Opening adjusting trade in CL so our buddy oil our pain our thorn oil So here the one that we added is this one here We entered a new strangle and look at this look at how much the implied volatility has expanded It's not too far off as far as the price of oil from where we put it on But implied volatility has expanded so much that it's put pushed our P&L lying down now I got a question From a couple people in the community is like hey, you know, is this is it a good idea to be? you know putting on a strangle in oil and Obviously nobody knows what's gonna happen and if it's not if it's too much risk for you for your account then absolutely don't do it This is a big contract, right? And we already have we already have one position on in oil So obviously do we wait we wish we would waited a few days because we would have got an even bigger credit But we're talking about a thirty three thousand one hundred fifty dollar max profit on one contract here So but that that volatility there, you know the risk the uncertainty that comes with risk So you've got to be comfortable. Don't just blindly follow our alerts because we're putting putting this trade on You've got it. You've got to make that decision for yourself But you know if we all can you know Ivy contracts, you know that P&L line will jump back up pretty quick And we got we got a really big range here because it implied volatility so high as well But you've got to you know do what do what's best for you the other the other thing I've been having a lot of questions for email community is You know, how how low can oil really go right? It's a physical product. It's a consumable product from Every country in the world, you know, how how low can it go? And you know, I was reading something, you know, I think the Saudi Arabia oil company I mean they can they can produce oil for single-digit per barrel, you know, so let's say $9 per barrel I don't remember what it was, you know, so could oil get down to $10 a barrel. Yeah Yeah, it could now. Do I see that happening? No, no, I don't But you know, you don't want to think oh oil could never absolutely never get to $10 a barrel because it certainly could now That would be just a crazy situation. But guess what? We are in a crazy situation right now So don't ever say never just stay small key and you know, again if it doesn't fit You can also go to some of these smaller ETFs like XLE XOP if you're not if you're not comfortable with the futures to so that's that now we also still have our Have our short put leftover from our other position So we just got rid of the call because it was pretty much worthless and we're just looking for a bounce So, you know, we were on a good good bounce yesterday up over 20 some percent And then now we're sliding back down down about 10 today So just kind of holding on to that until we get down to about 21 days to expiration Or if we you know if we get a decent bounce I would look to add that call back on and then just continue to manage that that short strangle But just being patient just seeing if we can get a little bit of a bounce here Obviously if it continues lower that's going to hurt that position. So again going back to that If you have this same position on two and you're not comfortable With that with that downside risk and oil on that short put then by all means get out or sell a call against it Or you know do do what you need to do to make yourself more comfortable All right, it's oil next trade Oh, that's where we close that call side of that strangle Closing trade in spx. So we had a weekly double calendar in spx. This was a really nice one closed for over $2,200 per contract Just held that for six days I know a couple people held on a little bit longer and got out even with even a bigger profit. So Great trade in spx and we put another one though those on today, which I'll get to you in just a minute opening adjusting trade in zw. So I mentioned I think on last week's video that we may just you know Bail on our our wheat trade just because you know, there's so much high implied volatility elsewhere But the reality is the juice in the options in wheat are good as well And and the more I thought about it. I thought you know what? I think it makes sense to keep our wheat position or you know Continue to extend duration on this wheat position because it's just such an uncorrelated asset class to the rest of the market You know, see we've got stocks. We've got the euro. We've got oil. We've got gold We've got net gas bonds and and wheat just adds another uncorrelated asset And we had on so one of the alerts here was we had on a short put vertical here That was in the money and we got this huge move up yesterday And came right back into range and so we ended up booking a nice profit on last month's Piece of the trade and then we went ahead and entered a new centered iron condor. So it's pretty close to where we put it on Um, it hasn't moved much. So just waiting in wheat So there's the there's the opening trade and there's that closing of that put vertical and then closing trade in spy. So we had an iron duck on in spy and price Came right down to the duckhead. We took this off this morning Um, I mean it was already to a point where we we got you know, we bought this back for 26 cents almost nothing Uh, we could have held on for a few more cents I know some of you were looking to get at it like I read in the community like 14 cents and and that kind of thing So that's great. If this was spx, we probably would have left it on longer and potentially just let it expire But with spy with the way the market is moving crazily Let's go to a chart um, I can't remember what our exact strikes were on that duck, but um, you know What I didn't want to happen was this thing to move out of range and then we end up, you know Closing it for 50 of max profit instead of whatever we did 80 90 of max profit. So, um Yeah, I just didn't want it. It was it was so well centered in our duckhead We just said let's take that profit and run and you know, now we're getting a big move So it probably benefited us by doing that But uh, you know if remember on an iron duck and I'll show you our iron condor position But the actual iron duck, you know, if this was a duck and this was the duckhead You know, if you if price does expire in between those short strikes Then you can you could let it expire theoretically and you just it would just uh You just get max profit the options go away But the problem is you know, this these we're having such huge swings I didn't want to get to a situation where we ended up closing between our Our short put and our long put And then we get assigned uh over the weekend and we don't have the other options in place because for protection because they expired So that's why we on on on american style stocks and ETFs We typically close those before they expire whereas with spx or rut we can let those expire because those settle to cash cashish All right, um Next trade rolling adjusting trade in dia So another rolling of one of our verticals, uh, and this one was already out in may with 56 days So we just rolled down our strikes from 250 255 all the way down to 210 215 so if we take a look at dia We've got two sets on here So we've got the one out in may that we're just talking about here We've got four contracts on that one and prices moved down even more since that roll And then we've got the one in that's still in april and again We're at a point where we can we can roll this one as well So early next week we'll potentially look to be rolling the strikes closer on that one and since this is in april We'll roll this one out to may as well So then we'll have two sets out in may one with three contracts one with four Next trade opening adjusting trade in spx So this is that weekly double calendar and we did the front week with seven days and the back week with just 10 So remember in and this is the one just like the one we did last uh that we just closed out this week as well So remember In our course when we teach that weekly double calendar, uh strategy in our week in our weekly income course Typically we're we're selling the front week at about seven days, but we're typically buying the back week out at like 21 days So in this environment, I've been shrinking the difference between that front and back week And I want to take a minute to explain this uh and why why i'm doing that. So if we take a look at spx So here's what that looks like For one thing, you know, this only costs 800 and some dollars in buying power So it so by shrinking the difference between The front month and the back week front week and back week You're you're reducing your buying power so you could get into this on spx for whatever it was 800 and some dollars So that that's one thing the other thing, uh, I'm doing a little bit differently is I'm widening out these strikes So we we talk about using about the 40 delta on each side in this case. I'm going between about 25 and 30 so we're just getting a wider range uh to to uh to help with some of these massive swings If we put a slices to break even The uh, you can see initially we have over an 80 percent probability of profit on this trade I think it's closer to 84 85 when we first set it up the prices moved down since then So um, so that that's kind of the difference and and so I want to make sure you understand Why we're why we're the other reason why we are Kind of shrinking that distance between the front week and back week When we when we talk about like a double calendar or a calendar spread in general, you know, we typically talk about okay If implied volatility expands that's going to benefit your trade Uh, or if implied volatility contracts, that's going to work against your trade but I want to make sure I clarify this because You you can you can get hurt on these trades For example, I put a similar one of these on in a in a different account in my personal account yesterday Well, vol is getting crushed today And so price is still pretty dead center But my p&l line is now down here because that because that vol crush So when vol contracts Significantly you can you can get hurt on these so there's no free lunch when it expands it benefits you But here's here's the real So it's not just a matter of volatility expanding and contracting and what makes these calendars a little bit more complex Is because you're working with two different expiration cycles And so for example on this one We are selling the front week which is that seven day and we're buying the back week, which is that 10 day So theoretically we want the front options to contract quickly And we want the back ones to either contract slower Or even expand right because we're buying those ones So we would we want those to expand we want these to contract typically what happens is the front just expand quicker Then do the back and that's how we profit off of the calendar spread So if you're looking at the seven day currently The volatility the the volatility on these options is about 86 and the ones in the back are about 76 Okay, so so it's really the the expansion or contraction of implied volatility the difference between these two that really matters Okay, it's not just if implied volatility contracts. It's not just if implied volatility expands It's how the different cycles work so One of the reasons that I am kind of squeezing the duration between the the front and the back in this period is because Um Three days is not very much, right? That's not a very long time. So the so the difference so when these expand and contract Theoretically they're going to move Together a little bit closer closely than would The back week if they were two weeks out, right? So the back week is two weeks out And you could say okay Yeah, but look at those they're way cheaper, right? So don't you want to buy them when they're way cheaper? Well, yeah, theoretically, but again, it's the difference between the ones you're selling and the ones you're buying It's not just that they're cheaper. That doesn't mean that they're going to expand more Well, this one is contracting. Okay, so it's it's the difference So the reason I like to do the the tighter duration between the front and back right now is because You know, I think these just three days apart. Those are going to move pretty similarly, right? So The front will contract The front. Whoops. Where's my pin? The front will contract at a rate like this and the back will contract very very similar Okay, so so then what we're left with is pure theta decay, right? So Theoretically our our profit tent would stay very similar and as we go through time To next friday, you can see the p&l line go up We're going to exit this either the day before expiration or on expiration date And you've got a this big range of you know, potentially capturing a big profit like the one we did that we closed this week So that's that's kind of the thought process now You know the market's going to do what the market does There's nothing that says that has to happen, but that's why I'm not going out as far on the back week right now because think of it is just From a from a human nature standpoint, right? So if uh, if implied volatility contracts There's a lot of juice in these back week options. So they they could they could can uh Theoretically they could contract much quicker Even than the front week So, you know, just so it depends on what happened if some kind of news comes out That says, you know, something's going to happen in a couple weeks. Well, that's that could affect the options out here where they could contract quicker than the back ones and so Anyway, that hopefully that all makes sense I'm just trying to give you a little bit more of my thought process of why we're kind of squeezing that duration right now as opposed to doing like the seven Uh in the 21 ish day kind of differences between those so Just got to understand the way that these work if you're going to trade them because it's uh, like I said, there's no No free lunch. You got to you got to make sure that you understand The volatility of the front versus the back, but they can be very profitable like we saw this week And um, and and you can get smacked around a little bit too like the one I put on yesterday involved contracted today Um, you know, I'm I'm under water on that right now and I still have another seven days So a lot could happen. So I'm not really too worried about it But you know, we and that's why I talk about we want to get in on these on days When implied volatility is contracting now the market is Lower now and implied volatility is expanding at this point. But when we put this on this morning Uh, it was uh, I mean the the cost of these double counters kept going down and down and down I was watching them for about for for a little while before we even put it on because they just kept coming down down down so, uh You're never going to time it perfectly You're never going to catch the bottom or the top of the implied volatility expansions and contractions But uh, anyway, I just trying to give you a little bit of insight and thought process behind the method to our madness Hope that helps All right last trade opening trade in roku. So we threw on a reverse ducky duck in roku and reason we did that roku was up today and Obviously with the reverse iron duck we have no risk to the downside So this thing could tank again. We got no risk there and we got all the way up to 87 80 To potentially get a duck head. So if we do get a rally into next week, you know, that could potentially come right into the duck head Uh, obviously, we don't want it to go past that break-even point And if we if it does we'll bail and say see a roku, but that is uh, that's what we've gotten roku Some of the other positions here. We've got six e which is the euro You can see prices just outside of our range there But if we look at the untested side still got a decent amount of juice in those calls. So we're not looking to Reposition those yet We've got, you know, we've got 49 days to expiration. So we're certainly not looking to roll out to the next expiration just holding that Uh, yes, I mentioned g c. Oh gc. Yeah, I want to talk about this one too So this is our iron condor Look at what implied volatility expansion has done to this puppy Uh, so we're just outside the range But look at how much value we have left in these calls that are they're almost at full value still And so we're just that's why we haven't adjusted this.  So as implied volatility has expanded, we would do it in the same cycle So we wanted to look at adding a Another potential gold iron condor because it has moved out of out of range and that would just a get us some more More premium more credit when implied volatility is higher But if I Sorry, my computer's freezing up here. Let me pause for a second and I'll come right back okay, so um, so if we go to if we were to go to So well, they're a little bit lower now when I was looking before the the short calls We're still right around that 20 delta So it's like if if I was going to do this I'd be using the same strikes and that's not what I want Now they've they've come down so we may look at adding one next week But at this point we're just kind of holding on and and seeing if we get a little bit of a bounce in gold Natty gas moving a little bit lower today, but we've got a the suggested short strangle So it's still a little bit in range here if we look at the calls still got full value left in the call So no adjustments on natty gas yet. We've still got 38 days to expiration. So noting to roll out in time Bonds bonds have been playing a little bit nice for us Obviously, we had that huge rip your face off rally that was pretty painful and now things have kind of come back in line And if we look at Where prices this is kind of both of our positions combined, but if you look at where prices It's not too far out of that out of that range Here's the one and if you look at just the untested side the puts again still got over full value left in those puts for theta decay there And then on the other piece It looks like this we're inverted and then you know the puts there Uh, you know, we still got a ton of room to row to run and then on the calls same thing. So No adjustments. There's nothing to do here There's no adjustments that you can do that will benefit this except we are waiting, you know We are still getting positive theta decay If we look at you know where our theta is You know, we're still getting We're still getting over 271 dollars a day in the theta decay So, you know, there's that we're we're just playing the waiting game and and we're at 35 days to expiration So once we get down to closer to 21 that we'll roll out And just continue to manage this thing. We might at some point once we You know potentially recoup some of what we're down in bonds We'll probably cut one of those loose So we just have less exposure and then we can potentially add one back on at a later point But at this point we are we're just playing the waiting game ZW I mentioned that Apple I can't remember. Did we adjust that one? We've got this long put vertical here prices hanging out right here. Just holding that for that short delta exposure I mentioned de it's down over 6% now just since we've been talking this moved down quite a bit S&Ps are down almost 90 now just in the time that we've been talking I mentioned dia IWM Roku smh spx spies Yeah spy. We got that iron condor still Vxx I mentioned xbi. So here's a this is an adjusted strangle again looking at the untested side You still got a lot of room to go in those calls But late next week early the following week We'll be rolling this out to the next cycle and then lastly xlk another short delta position About at 50% of max profit here. So again, we'll potentially be rolling this out to I don't think there's any may options yet Yeah, there's no may options yet. So we're just going to hold on to this one for now Until those come about and then we'll potentially roll out We could also consider rolling out to the weeklies, but in xlk. I don't think these are that liquid. Let me just check that out For some reason my Platform is a little freaky today Yeah, the the liquidity is not great in those weekly options. So I'd like I'd prefer to wait till a may monthly cycle comes out Um, yeah, I mean, these are these are a buck wide over a dollar wide at the money. So We'll see what happens. We will just hold on to that for now Everybody have a great weekend and we will talk to you next week


Dyma, mae'r ddysgu i'n'r llwyddon â'r club sy'n gyferio eich cyfnod i'r llwyddon, ac yn ddechrau'r Lleiffwyr yn Lleiffwyr, ac mae'r ddodol i'r Prifysgol a'r Lleiffwyr yn ddoch yn unig i'r llwyddon a'r llwyddon sy'n ei hyn sy'n ei chanfod i'r llwyddon â'r club sy'n gyffredd yn gyferio'i phir. Mae'r ddodol i'r ddodol i'r llwyddon, ac mae'n cyfnod i'r llwyddon i'r Lleiffwyr yn gyfnod i'r llwyddon? Mae'r genedigbu'r rhadion ffeyddai'r pelyddio'n cymdeithasol ym môl eisaugh, ffeyddai'r pelydd iawn, ac mae'n he boa i ddechrau'r cymdeithasol. Fydo fyddwn i'r pelyddio'r society. Mae'n hefyd i eisaug. Rhaid i'r pelydd i'r company. Fydo39 i'r cwymdeithasol. Mae'rodge piadwyr dda wedi ddod oeddoeddwyd oherwydd rydyn ni'n gweld â phuedd ffeyddio'r cydanows. Yn ei wneud eich gwelio hir, ac mae'r Fyad dda oddi i'r fan, is meant me to bring off engagement for first year for first year reps in societies at the moment to make sure they know each other and know their role in society and give them an opportunity to shadow all the other committee members. What I love to see is first year coming up and being first year in rep and being chair of it because they loved it so much, which is a huge thing. New societies have emerged this year such as the Skolio's Society and Stand, the already popular Suez. DCU president Brene MacBrach call down to the clubs and stocks fair to see what his students are doing outside their academic labs. I come to clubs and stocks every year. It's always fantastic in this sense that what students are interested in and what they're doing is a huge blow at the holidays. These were challenging week. Close to a hundred societies this year. They're going to bring us over 150 clubs and stocks, and it seems to the whole panel of new ones, and it won't let me join up which is really annoying. DCU's engagement with clubs and societies is what makes our college unique. Whether it's having tea and chats with a hangover hub for the sober sock or going surfing on the weekends, they have something for everyone. Alison Clare, DCU TV News.


Don't worry, buddy. I will repair I will repair south and when they just came from You don't have a base over yellow amplifier. That's the one that yeah, oh Wait, it says a and there's nothing. Oh, there is something there. It wasn't rendered for me That's my excuse and that's what I'm gonna stick to I don't know how to get to the top of this building There it is. I will snipe from the south You did I am helping that trees in a way Go into the top a treed. Oh, this is no fun. I'm coming to the action I'm missing every shot. Yeah. I'm gonna I hold it You can't escape I See you coming from the backside Anakin Cuz I had the high ground I'm doing it. That didn't help at all. We're breaking your face Cool cool cool cool cool. I'm gonna back up a tad. I Cut out for this close quarters. I am gonna deploy a century Build the century. I don't have a century until 10 seconds This will have to do zapper zapper zapper They don't last that lasts like two seconds. Oh, that's why I don't like oh, I like it when it has both Bear and the zapper and I think that one just has a zap. Yay. We did it We did we did we did it. I got a lambie aka a llama I'm gonna get some duplicates chat. I Just need hero XP man Give me that hero XP's That yeah, I think that is hero XP. I Remember this yeah It's going right I don't know. I think hero XP is white and blue Okay, I got a lot of survival not that much hero I got some though Okay, I believe you We will upgrade you Can I evolve them? What is close changed? Where have I been? I have not noticed this with other people Well, what did Jonesy do? Did he get more of Skeleton II? I didn't notice anything different when I upgraded him hmm Or at least he's two-star now, so I get the Anti-material charge. I never use that at all It helps to farm nuts and bolts with that you could just like punch it. Oh Really? I just actually switched my um farming to doing that. Oh Willy The Chinese food delivery guy actually are our delivery guys never wear hats. Yeah, what do I have to do next? I'll do that three more time, huh? Two more time whatever select quickly launch Need more lemmets aka llamas Jamas Jamas Deliver the bomb my favorite I don't know what's going on, but it's fun to watch All right, so if I hit the X button in here you like Yes, who's got a short cooldown Yeah, I'm doing that from now on Yeah And it's back up. Okay, I missed everything. Yay Lost all my shield doing that Ow Funny game do it. I just Falcon punch the semi truck Okay, that's why you had six billion nuts and bolts. You just run around punching everything my tail mum Got to get anything from that gotta punch the right things just punch the semi It's cool. That's fine B. Okay. I'll have a little go my goodness. Oh Cakes are back on the menu boys. I get my tickets. It's only a few hours left before the birthday goes away 3 a.m. And we're toast Really, yes 3 a.m. Tonight. Yes. Yes That's not funny, I may have to buy the 7 7 llamas The one that's in the store now. I gotta see what you're talking about. I don't remember The one that a lucky 7-1 the one you asked me if it was worth I'll take you worried for it. I don't remember It does sound like something I'd say Somebody's somebody chat so that I had I had memory like a fish I'm beginning to agree with it. I mean you just asked me If I would buy that llama No I'm a fish You want a llama loot llama? Oh, I did it. Hey Mine don't have bullets because I'm not cool. Is that a node on the skill tree? No, it's actually a survivor. Oh, it's a perk of the type another hero Oh, no, it's not him I want that though. I know is that grizzly or the other dude? Vanguard Vanguard south. Yeah, I need the bullets man. I forgot how to dance Ooh the framerate dropped there. I'm trying to be nice. I'm not running fine. I'll take it all All the bullets Dear goodness, this is so good Like who needs nuts and bolts when you can just do this I have been wanting that like the entire time because I miss the event My first llama that I opened I got A birthday llama.  I regret nothing All right, I'm here What all these the the square Yeah, oh, I just I just Okay I guess it makes sense since they're cars Um, I mean car yard So make sure to get all those Yeah, what? All the car yard like the old car yards Okay, I thought you saw one Okay Zip zips about but I fell in the water again What we supposed oh, this is the deliver the bomb one. So we need blue glow Somebody's throwing baseballs At me Ha looks like lad is back on the menu boys And I don't like trucks What I just say about trucks I don't like them gun blazer southy man I probably melted one down. I probably had a blue one or something Not a blue one like a green one gun blazer southy What up ghost graded if you do? Yeah, I definitely will upgrade if I get another one So you melted it down or I may have I don't know. I said I may have melted one down Go away Ghost in the bud. Everybody show some love. Is that four months in the road? Thank you so much for the support And good evening. Good morning. Good afternoon. Good morning Time zone appropriate salutations. Thank you so much Blah blah blah blah. I really need to figure out this mission. Where'd you go? I'm building on No, I'm talking to this ghost Trying to snipe him. That's the wrong button. That's the wrong button. How do I hit alt z? With one finger I managed to hit alt z with one finger. That is amazing I hate the z button. I just I just don't like it It's all over there in the corner weird fingers Those are fingers I use to eat pudding Okay, what are we doing?  It might be All right. Y'all got one job over there. Okay Now I've done all this work I buy all this work. I mean none I gotta smash more trucks We must push a little cart I forgot how to dance Remember the key We're getting type slash Dan But I think it's B We're so outdated We've got a total of two dances and save the world and in br they have 6,488,306.4 dances We got two two Do you know how much dancing is required for save the world? We have so much downtime we could dance like I'm serious We got dance offs while we're building To see who's going to who's going to donate all the metal By the little cute emo I mean when the guy comes out and goes I am a bear you could be like, yeah break it down and you start dancing Epic are you listening? We demand more dances and save the world Or we will protest You know we'll do we will build nothing but wood structures for the rest of the game's life Okay, why this thing stop? Okay never mind. I'm confused Level one structures Level one wooden structures and we will complain that we can't win and we will spread the word that this game is too hard It will be the ultimate false advertising fake news dot 3.0 Leave that alone This this Awesome animation no clip No clip just going to go through this wall physics.   I keep thinking that's a This is a lot of dudes Oh It's time to break out the typewriter And if I need dissertation I am in the process of ride the feces On the intricacies of save the world zombies and their effect on traps and bears Where's the whiteout? I need correction tape a stat a sap My s key is stuck I will type a five instead And I will tell the professor of my woes No, but seriously I I'm not like I'm being semi. I'm joking a little bit about the thing, but I can't wait till they bring all that stuff from br over here I'm talking about dances and skins and all that stuff. It's like If they can just if they could just bring like one tenth of that content over here I think more people would play br. I mean we'll play save the world Especially if there's skin incentives behind all these challenges these these dailies Can you imagine if you got a new skin if you did dailies? People would never let this game go. That's why people play br man I was talking to my wife about this the other day guys I was like the reason br is so popular is because they have been they have created an insane amount of content for you to grind for And every time you think you have gotten it all they introduce a new season with 700 more skins And 300 more dances that you just absolutely have to have They are pumping out so much content that it's kind of unprecedented That's why people love fortnight br so much man It ain't because of the game no more. It's because of that grind people are actually tired of br They don't want to play br, but they want them skins They want them dances That's the way I feel about it Those are my personal thoughts chat. I can't place it. Are they real?   You better believe it They got to have it And then it's not like they're low quality skins either. They're really high quality High quality dances and high quality skins The epic is pumping out. It's kind of amazing any game that has such great dance and we play tf2 We play years of tf2, which was like top dog and skins and and emotes and stuff Which still are kind of unprecedented tf2 has some amazing stuff But this game I've never they must have a dedicated dance team of motion cap Just they just pump out all these new dances like it's nothing And people eat this stuff up I mean I I was watching because I don't play br. I basically play it through watching streams I was just watching people they were going through pages and pages and pages of skins I was just like how many skins are there? And dances just like okay. What am I gonna do today? What am I okay?  They got to see it in real life Tell you man epic they deserve all this money because i'm serious. They they made the right move people were Saying it was a mistake to move all those assets off of a paragon over to uh Over to fortnite you guys remember that when they cancelled paragon and they They moved all those people over here and all of a sudden Seven billion dollars later. It turned out to be the best decision. They could have ever made Okay, we gotta do one more Wait, I got points now. Hold on uh skill tree And I choose you peak. Wait. I already got that. Um, I honestly don't know what to get next Because I can get traps here Three star trap evolution Yeah, yeah, I'll do that Aim towards the hoverbot. I thought I already got the hoverbot. Where's the hoverbot at? Soldiers up top. So I thought hoverbot was up here


Good to see you guys. Let's get started. So today I'm going to spend a bit of time teaching you guys about how to do classification by modeling the posterior probabilities. So the idea is that we have a number of classes that we wish to identify our data into, build a model of those classes. And the way we described it is that we have a likelihood function. We have a prior probability. We form a posterior probability. And today what I'm going to show you is that we can write the posterior probability, the ratio of class 1 to class 2, class 2 to class 3. The ratio of the posterior probabilities, the log of those can be written as a formula that depends on the input x. And if the variances of the classes are equal, then the posterior probability ratios is going to be a linear function of x. If the variances are unequal, it's going to be a quadratic function of x. This is assuming that the distributions are Gaussian. And then at the end of the class, I'll show you what to do when your distributions aren't Gaussian. So for example, you have some collection of data and you have some arbitrary distribution. And you want to know how do I build a model of the posterior probability for these. And this is called kernel density based estimate. Basically the idea being that we're going to put a little kernel at every data point that we have and the sum of these kernels forms a density function. And then using that, we're going to be able to classify our data. In fact, the homework for today is classification using kernel density estimates. So to start off, let's go over what we have as our data. We have some vectors x and we have some labels y. And we have n of these. And these y's belong to some classes, maybe 0, 1, you know, L. L number of classes. And our objective is to build a model that can allow us to dissociate between the various classes. And to give you an idea, suppose that we have a two dimensional problem and we have, you know, x1 and x2. And we have some x1's and we have some x2's. And when we build a classifier, what it's going to do is to separate these two into regions. And so for example, if we have a system by which the likelihood functions are Gaussian with equal variance. If this comes from the same variance as this, then the classification is going to separate them via a line. And today we're going to see what the equation for that line is. If on the other hand we have a scenario that looks like this, suppose that we have another class. Suppose we have a blue class as well. So suppose I also have something like this. In which case now I'm going to have another line that separates this.   And these lines that I drew, I drew two lines here. This line, this line 1, line 2, there's going to be another line as well. Let's call this line 3. What these lines are, are the ratios between the log of the probability of x given that y is equal to blue times the prior probability of y is equal to blue divided by p of x given that y is equal to red times the prior probability of y is equal to red. So that's one of the lines. Then I'm going to have another line, p of x given y is equal to blue, probability of y is equal to blue divided by p of x given that y is equal to black times probability of y is equal to black. And then finally the third line is going to be the probability of x given that y is equal to red and prior probability of y is equal to red divided by, so I have red and blue here. What I need is p of x given y is equal to black times the probability of y is equal to black. So the three lines are going to be these three ratios. And I'm going to show you that these ratios are indeed linear functions of x. So this is the case if I'm assuming that the probability of x giving that y is equal to some class i is a normal distributed with mu 1 and variance sigma and probability of x given that y is equal to j is normally distributed with mu j and the same sigma. So equal variance. If this is the case, if my likelihood function looks like this, then my class identifiers are going to be separating the classes based on these lines. And I'm going to show you why that's true. So in principle, if you wanted to classify what you'd do is that you'd say, all right, compute the probability of x given that I belong to a blue class, the likelihood times the prior probability for each x here I want to compute this ratio. And if it turns out that for a point out here that the log of this function is positive and positive here, so if it's positive for this ratio and positive for this ratio, then that means that the likelihood of it being blue, sorry, down here is what I meant to say. If a point down here has a likelihood that has a ratio that's positive for this one and positive for this one, then that means that this most likely belongs to blue. So for each point you compute the ratio of the likelihoods for that class to every other class. And if it turns out that for that class it is higher than every other class, that means its posterior probability is higher. So let me show you why these are going to be lines. So what we're going today is that we're going to start with the simplest case where the variances are equal and the classifier is going to be linear. Then we do a condition where the variances are unequal. And in that case, we're going to see that the classifier is going to be quadratic. So it's going to have shapes that are going to be not lines but quadratic functions. And finally we'll do a classifier where it's not Gaussian at all. It's some other function. And there you're going to see that it just becomes a very complicated thing that depends on these kernels. Any questions? Okay, so why is it that the ratio of the log is linear when the likelihoods are Gaussian with equal variance? Well, let's look at what this is. What's the log of p of x given that y is equal to class 1? So if we begin with a vector representation, so that we have this normal distribution is a vector, what I have is 1 over the square root of 2 pi raised to the power of m where m is what? m is the size of x. Where sigma is the variance times the exponential minus 1 half x minus mu 1 transpose sigma minus 1 x minus mu 1. So that's the normal distribution associated with the vector x of size m. So what's the log of this function? That's equal to minus 1 half. We have this term here, which is going to be minus m over 2 log of 2 pi, minus 1 half log of the absolute value, sorry, log of the determinant of the variance-covariance matrix.  So similarly, when I want to write the distribution associated with some other class, say class 2, log of the probability of x given that y is equal to 2 is going to be equal to exactly that, except that the mean is going to be now mu 2 rather than mu 1. Okay, so I have the likelihood functions. Now, what about the prior probabilities? So the prior probability of y is equal to 1 is going to be something called, let's call it q1, and the prior probability of y is equal to 2, let's call that q2. Okay, so then the log, what's the posterior probability? Probability of being, having class 1 given x, that's equal to probability of x, given that I have class 1 times the probability of being in class 1 divided by p of x. So this is the posterior probability of being in this class. Well, when I want to find the ratio of the posterior probabilities, the log of that, log of the probability of y is equal to 1 given x, divided by probability of y is equal to 2 given x, that's going to be equal to the log of the numerators, right? p of x given y is equal to 1 times probability of y is equal to 1, divided by p of x given that y is equal to 2 times the probability of y is equal to 2. So the ratio of the posterior probabilities, their log is equal to the log of the ratio of the likelihoods times the priors, because the denominator or p of x, the marginal, is going to cancel out. So let's see what we have here. So we have the log of the likelihood functions that I wrote here, and I also can tell you the log of the prior probabilities. So this is going to be equal to the log of the numerator, which is log of p of x given that y is equal to 1, plus the log of probability of y is equal to 1, minus the log of p of x given that y is equal to 2, minus the log of the prior probability, right? Okay, so this is just log of q1, this is log of q2. So what I really need is this log minus this log. So I have written that these logarithms appear for you. Here's the log of the likelihood for being in class 1, here's the log of the likelihood of being in class 2, and you notice that when I subtract them, let's see what we get. So the log of p of x given that y is equal to 1, times the probability of y is equal to 1, divided by x, y is equal to 2, times the prior probability of y is equal to 2. It's going to be equal to minus 1 half. I'm going to have x transpose sigma minus 1, cancel x transpose sigma minus 1. I'm going to get y1 transpose sigma x minus y2 transpose sigma x. Let's see if that's right. Yeah, looks good. So that's equal to, you notice that x here is a linear function, I have minus 1 half mu1 transpose sigma1 minus mu2 transpose, the inverse of the covariance matrix, plus this is a constant and this is a constant. So I'm going to call that w0, which is equal to some vector w transpose times x plus w0. Yeah, sorry. Yeah, so there should be a 2, let me see, there should be a 2 here. Yeah, thank you. Okay, so what this says is that the ratio of the posterior probabilities is a linear function of x, which means that the decision boundary where what's happening is that the log of the ratio is equal to what? At the decision boundary, what's the log of the ratio? What is it? Zero. Zero, right, because the top and bottom are equal, right? So log of 1 is zero. So one can compute the log of the ratio if one knows the mean of each of the distributions and the variance. And if the variances are equal, then it turns out that the ratios are going to be such that it can be represented as a linear function of x. So what one does is that if one assumes that the two distributions or whatever, however number of distributions there are, if they have the same variance, then this quantity, so say that I want to know the log of the ratio between blue and red. Well, what I need to know is the likelihood for blue and the likelihood for red. And any x, for any input x, I can compute the log of the posterior ratios. So then what I need to know is, okay, which class am I going to say this data point belongs to, the class for which that log is larger, positive. I compare class 1 with class 2, class 1 with class 3. If the ratio is greater for 1, it belongs to 1. All right, so now let's do another example of this. Let's do an example where, in one dimension, what this means, before I go to two dimensions, sorry, before I go to unequal variance, what this means in one dimension is that if I have some likelihood function that has been multiplied, so this is probability of x given that y is equal to 1 times the prior probability of y is equal to 1, and I have another p of x given that y is equal to 2 times the probability of y is equal to 2, and the variances here are the same. So the variance of this is the same. The reason why this is lower is because this prior probability is lower. So the decision boundary, of course, is going to be here, and if I plot the log of p of x given that y is equal to 1 times the probability of y is equal to 1 divided by this. So if I plot the log of the ratio of the posterior probabilities, what I get is a line that crosses at the decision point. That's when it's equal to 0. On the other hand, if I have something that looks like this, if I have one distribution that looks like this, p of x given that y is equal to 1 times the prior probability of y is equal to 1, and I have another distribution that looks like this. This is p of x given that y is equal to 2 times the prior probability of y is equal to 2. So clearly now, the variances are different. So the variances of 2 is much larger than variance of class 1. So what are the decision boundaries here? Now if I were to, so my decision boundary is here, obviously here, when I'm out here, I'm going to say this belongs to class 2, belongs to class 1, belongs to class 2, right? Okay, but what does the ratio of the posterior probabilities look like? So the log of p of x given that y is equal to 1 times the probability of y is equal to 1. So I want to plot this. What do you think this looks like? Let's begin out here on this side. Is it going to be positive or negative? It's going to be negative. Why? Yeah, 2 is bigger, right? So it's going to be negative down here. What about here? It's going to be positive. What about here? Yeah, negative. So it's going to look like this. It's going to be a quadratic function. Let's show that it's going to be a quadratic function. All right, so what we have is we want to compute the log of the probability of x given that y is equal to 1 times the probability of y is equal to 1. And we're going to assume that this probability, the likelihood function, is a normal with mean mu 1 and variance sigma 1. Okay? So the only thing that's different than the experiment, the derivation that we just did is that each of the likelihood functions are going to have their own variances. So this is going to be sigma 1, and the second class is going to have sigma 2. So the log of this function, let's see what that's going to be. So we have greater of the exponent minus m over 2 log of 2 pi minus log of the determinant of the variance covariance matrix. And then we have the log of q1, where q1 is this probability. So let's simplify just a little bit. All right, so what I want to know, what's the log of this ratio? That's going to be equal to, so this term below is going to have a different variance. And then this term here, minus 2 x transpose sigma 1 mu 1 minus, although it doesn't really matter, just more convenient to write it this way, minus 2 times mu 2 transpose times x. And then I have the differences in the means. And then some constants to add at the end of it. These logs are going to add to the end of it. So that's going to be minus m over 2. That's going to cancel. I get minus log of, does that look right? Yes. Okay, so this is a quadratic function of x, right? So I have some terms here, right? There's a quadratic function of x. Then I have a linear function of x. Then I have some constants. So this is equal to x transpose w 1 2 times x minus w 1 2 transpose times x plus w 0. This is a matrix. This is a vector. It's a matrix, a vector. And in this case, this is a constant. So I get a quadratic function of x. That's the log of the posterior probabilities. So for example, if I were to, let's try three classes that we can now draw the decision boundary. So I have x 1 and x 2, and I have some black dots, some blue dots, and I have some red dots. If I were to do now the ratio, so what I'm going to compute is the probability, the log of the probability of blue over the red. This is what I mean, the probability of the posterior probabilities. What I'm going to get is for each x, I'm going to get a number, the log of the posterior probability. I'm going to assign it to the class that it has the largest ratio. And the decision boundaries are going to become quadratic. So for example, for blue, I might get something like this, so forth, and then as this follows. So I will be able to separate out a region, a quadratic region associated with one, and then other regions associated with the red and blue. So the idea is that you don't need to compute at each point the log. The posterior probabilities, you model it basically as a close form relationship between the variances and the means. So those W's tell you what the posterior probabilities are going to be, the ratio of the posterior probabilities. Okay, alright. Any questions about this? Alright, so let me now spend a minute telling you about what to do when your data is not Gaussian. So our problem is that we have some data that we've collected. Let's begin with a one-dimensional version of this. And we can't assume that the distribution is Gaussian. So my problem is I want to formulate the probability of X given that Y is equal to 1.  So here's X. And when I look at my data, so I have one data point here, two here, three here. Something that looks like this. So maybe it's even worse than this. Maybe I have a couple of data points out here. So clearly it doesn't look like a Gaussian. This is my X given Y. So I want to represent this with a density function. Why do I need the density function? Because I need to be able to describe the likelihood. So how do I do that? Well, the way to do it is to plop a kernel. And I'm going to show you what a kernel is at each data point. And when you have a data point, you would just plop a kernel on top of it. And the more data points you have, the more kernels you build up on top of each other. And then what happens is that you need to normalize the whole set so that the integral of your distribution is one. So that's what kernel density estimates do. So our kernel here, kernel as a function of U, so I need to separate what U is from X. So suppose that U is my variable, and kernel is K. And we're going to describe what this kernel is. Kernel is going to be just a Gaussian sitting at a particular data point U. So this kernel is just something that I'm going to have at the data point U. So when I say form a probability p of X, suppose that I take all my data points that belong to class one, and I'm going to now formulate my density function as follows. I have n data points that belong to class one. And I'm going to sum up all the K's where each point for where I plop my kernel was on top of my data point. So this is going to be X minus Xi divided by H. So this is function of U. This is how I define U, K of U. This function is described like this, like this. And for U, for each data point that I have, I'm going to give it this function. What is H? What H does is the smoothing of this kernel. So this kernel is going to be really sharp if H is small. It's going to be broad if H is wide, right? So if H is large, it's like a variance. So if H is large, what you're doing is you're plopping a kernel that has a lot of breadth. If H is small, you're saying I'm going to have a kernel that's really sharp. What that means is that when you end up computing your density, you're going to get things that look like this. If H is one, you're going to get something that looks like this. If H is two. And everything in between. It depends on how sharp do you want your density function. Yeah. So like if your X is quantized, how far are you hitting? Exactly. Okay, what about if you have a multidimensional X? Then what you have is that K becomes a function of this vector U. And that's just equal to... So the usual normalize Gaussian. And then this P of X, given that you belong to class Y. So probability of X given that you're having some class is going to be as follows. So this is all the points that are in class Y is equal to L. So now instead of summing up one-dimensional Gaussians, you're summing up M-dimensional Gaussian where M is size of vector X. And H again is our... I'm sorry, this is K, a function K. And H is our smoothing parameter. Okay, all right. One last topic to tell you about. Sometimes when you're doing this kind of analysis, what happens is that you end up with a data point that's missing some values. So say that you are... So I want to tell you about missing or bad data. So you're doing classification and you have some vector space that you're trying to classify. Say that we have this two-dimensional space. Then we have X1 and X2. And then we have some data point that's missing some component. Say that we are missing X1. So we pick a point and one of these things is there and the other one isn't there. What do we do with that? How do we classify it? So let me show you the process. So suppose that we have a number of classes. So we have some class out here. It's called as class 1. So what am I plotting? I'm plotting P of X given that Y is equal to 1 times the prior probability of Y is equal to 1. That's the numerator of my posterior probability. Say it looks like this. It has a center sitting out there. And I have another class out here and I have another class out here. This is class 2. This is class 3. These three classes. So suppose that you give me a data point. And the value for that data point, I have the X2 value. Here it is. I have the X2 value for it. But I don't have the X1 value. So what do I do? So let's consider two approaches. So my problem is that I am missing X1 for some data point I. I'm missing this component of my vector. I have a bad data point. So suppose that we do this. Suppose we take the expected value of my data for X and replace it for the part that I'm missing. So if you look at this distribution here, what's the expected value of X1? Approximately where is it? In the middle. So someplace out here, right? So if I were to replace my missing data point with this value here, which is the expected value of X1, what happens? Well, then I end up with some point out here, right? That becomes my point. Then I would say, well, that belongs to which class? Class 2. Okay, but that's wrong. Let me show you why that is. So if you don't have that data point, you can still make a classification. Why is that? Because if you were to compress everything now to X2, so you don't have X1, right? So if you were to compress everything to X2, what you end up with is a distribution that looks like this. This is 1, this is 2, this is 3. So if you just look at compress, draw the distributions over over to one side, find the marginal to one side, then what happens is that the point that I wanted actually belongs to class 3. So this is the intuition. I'll show you the math why that's true. But the basic intuition is that when you're missing a data point, you can still make a decision by integrating out the effect of the variable that you're missing, the component that you're missing. So if I'm missing X1, I can still compute the probabilities based on X2, which means integrate out X1. So project everything out to X1. Here's what the distribution looks like. I have a blop at 1, a little blop at 2, and a blop at 3. Well, my data point is sitting here, which is the center of 3. Okay, so let me just show you why that's true. What am I going to just do? Okay, so my vector X, I'm going to classify as good and bad. So there's some component that I have that I like, I'm going to call XG, and some component of it that I don't have, and that's my bad component of it. So probability of Y is equal to being some class I, given that I have some good data, is the joint probability of being in that class and X good divided by probability of X good, which is the integral of P of Y is equal to I X good, X bad, if I take out XB divided by P of X good. So I just wrote the base probability as the joint probability divided by the marginal, and I'm going to, this X good is the same as this with X bad integrated out. So this quantity is just the joint probability I can write as P of X, given that Y is equal to I times the probability of Y is equal to I times integrated out DXB, X good. So what this is, this term, the numerator here, what it's doing is that it's saying to integrate out the effect of the dimension XB, which is the bad dimension, which is what we did here. We wrote the likelihood times the prior probability after we integrated out the effect of X1 by projecting the data over to X2, which is what this numerator is. So that's the posterior probability, given that you only have good data.  Alright, see you on Wednesday.


shave every 1000 here as you can see we're on the river we'll do a little fishing day I don't know if I won't catch anything hopefully we will start about the wind and the phone so we just got here we went checked out a couple other places no good you just you know so shallow and it just so we decided just to come here to our old spot hopefully we'll catch something it's a little after two I think so you know not a great great time to be out but you know we should be able to get some hits so stick around and kick you back on as monkey said when I catch something hang tight I didn't set the hook I don't think okay it was a gar I know it was a gar yeah I told you don't reel in reel out and he was big too okay guys so update I've been getting all kinds of hits she hasn't had that many hits but she had two fish one fish was kind of small probably just a couple pounder it got off of her line and then she had that probably 24 28 inch gar just now it broke her line so that's the closest we've got to catching anything so you know like I was telling her they you don't actually hook them they your line gets wrapped around their beak really and they got them teeth that come out the side and they go like a little cut your line real easy so but yeah they're hitting all right so keep you back on in a minute we'll do something now I'm pulling and reel out and pull I got something biting on that right there it's barely in the water and we didn't bring the net guys so I get something here I'll have to take him around yeah you had a gar on it wasn't super huge baby probably go 24 to 28 inches yeah but he's not like really fighting fighting but he's pulling could be a gar it's kind of pulling like a gar going against my drag and you might want to bring yours in because I'll probably have to go around that way call me the turtle man okay guys sorry it took so long to get my camera man to do any camera manning she's what I gotta get my camera but I'm the one catching the fish well turtle in that case alright put another hook on took out my bait though well I guess it counts I did have him in on shore so I'd be back with you update I had something on here I don't know what it was man but I was fighting in and snapped my you need to tell the truth all right truth is I was reeling it in not a fish on it I was just reeling in yeah I was just all I was doing was reeling in to recap yeah so we're thinking maybe I you know I don't know for positive but anything I can think of is that turtle you know cracked it and then I casted a few more times and that probably made it worse and then I just reeling in and snapped lightning rod shock yeah I'm shocked it's a Berkeley Wow Berkeley's expensive stuff well decent stuff I mean it's not you know but I'm just gonna I guess I'm gonna have to get a but jeez I mean what these guys use for bass fishing and stuff I don't I don't understand it but there it is so well it's fiberglass well get a kit okay well you want me to buy a $40 kit to try to fiberglass this rod that I can buy for 20 bucks yeah I can fix it but it doesn't make sense to I mean if it broke I don't want that well even if it didn't I don't you know I don't want to use this rod no more at least you know I still got my reel so we was talking that's third rod and one reels what I've lost well I didn't actually lose two of them two of them broke this one and that one broke but the one I lost because of a fish because I was getting you bait but it I wasn't getting a bite I mean I just casted in and I reached down well I had it under my arm like this it yanked it out of my arm and I went to reach to get her because it was in the boat to get her piece of shrimp gone I mean it was just like somebody just yanked it out of my arm it was gone well it had to be a big fish because turtles are slow this thing just grabbed it and went no I mean it was gone it was just like I said someone yanked it out of my hand I had it in my arm like this tight too because you know we're we're in the Gulf of Mexico so big fish out there right and it did it it hurt so alright guys I think I do have one or two on this camera on my body camera got a little fish this is the third one this is the third one this is the third pole huh yeah and we bought that these two were bought brand new remember the one that broke in Crystal River yeah you got that one right or did you get the orange one you know cut a little red red belly monkey had one on but it got off I can't get her to set the hook she just waits and just starts reeling she won't set that hook I don't know so anyway I keep you updated he got snagged turtle number three don't call me that keep telling her don't call me turtle man game off here he got snagged somehow hey there he goes okay guys so that was pretty much our fishing trip yeah so oh well I'm still one upload because you know everybody just only uploads when they catch stuff but you know you can't catch something every time I mean we caught some things but yeah that's pretty much it I wish I'd have been rolling when that rod broke I might have been because remember I sat here I was recording for a while and didn't even know it I just have to look down and my light was red blinking I was like shit I'm recording are you really I'm sending a recording jack shit yes yes so we're gonna go as you can see it's getting later what time is it mom a little 740 time too time to go home get something to eat we won't be eating fish it costs me money every time I go fishing well us money not just me or do many every time I'm buying rods reels tackle oh and then what 20 minutes ago I went to make my last cast I cast and snap the line snapped for no reason the line just monkey didn't want to film she's like well I want to get my camera like look it's my thing monkey wants a new boat don't you monkey yeah she wants an upgrade on the boat because she wants to go a little farther out in the ocean well the golf not not the ocean but the golf something a little more stable well we've had our boat and golf she's worried about me pulling that road lifting the motor up I don't want to sell that but I love that but yeah but that that boat can sit out back and not eat a thing because it's a boat you're gonna have problems so if we have let's say a water pump issue and I order a water pump you want to go fishing boating see we'll still have the old rich line sitting there see what I'm saying there's a lot of times we could have used two boats well we had two boats of one they've had three since we've been together I mean it ran it just it needed interior but we needed the money so we sold it so we're looking for another one about that size looking for around 18 foot yeah just upgrade so we knew but we don't want something too big to go in here I mean it's a river you can take bigger boats in here but we like to get back in them channels so even if we get something that we can't really take back she wants a regular boat maybe a center console or something but something that you know it's what I'm saying if we want to go back in and coves and stuff we can always bring that our boat the little boat I don't know we'll see just kind of kicking it around looking seeing what's out there right now but you never know something might pop up for good deals around six grand gets pretty good deals on some older boats 80s but we're talking Mako you know boats like that all right guys well thanks for watching I appreciate it she buried them at the man legend gone for now we're gonna pick up our stuff and I'm gonna throw this fishing rod into the trash can up here I got to thinking that's the fourth that's the fourth rod I got to thinking about that because the one the rod didn't break the eyes broke on and you can get eyes and you know the loops that you can replace them I think that's what I was going to do with that one it's got my Zebco on it alright guys again thanks for watching appreciate it got the weekend coming up so y'all enjoy and be safe we'll see you in the next one bye bye guys and take care monkey took her stuff up to the truck she won't know I caught this until after she sees the video four fish and three turtles


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A listening session by Minnesota Compass in Brainerd today focused on the issues and strengths in the Brainerd region. Sarah Winkelman has the details from the discussion. Listen, learn, and understand where the motives behind today's discussion and how to best represent the Brainerd region in data form. I was fearful that this would be another entity that comes out and tells rural communities as to what they have and how great they are and how they're growing, but would not seek the knowledge and the experience of local people. I was really grateful to hear that they were valuing those opinions. Community members voiced their opinions on the strengths of the area, including great location and natural resources, but also took time to speak about the issues. Portability and availability of childcare is a huge issue across the state, and then all of the connections that were made here today about how that connects to retaining and attracting workers and workforce issues in terms of ensuring that the right skills are here in the region. A workforce discussion that branched off into workforce housing needs. Virtually everyone who came today is talking about the same challenges. We have lower than usual median household income, which means we're more competitive. When asked what data would be helpful, questions arose like what is the real cost of housing, what is the typical debt load, and what wage do people really need to earn in order to meet those childcare and housing needs. We will be incorporating all of this feedback going through, as we talked about earlier, where there are themes that overlap, where there are maybe regions where there are differences in issues and strengths, and we'll think about how and where we can incorporate the suggestions for data needs. After discussion about what data might be helpful in the future, participants get a chance to explore the Compass website and look at some current data. The online resource is available to the public, where based on today's discussion will continue to grow with more resources. Reporting in Brainerd, Sarah Winkleman, Lakeland News. In 2018, Minnesota Compass will launch a new tool on its website focused on data in rural areas. If you've enjoyed this segment of Lakeland News, please consider making a tax-deductible contribution to Lakeland Public Television.


Hi everyone, Joe for Jaspy's CaseBreaks.com, coming at you with a random number block randomizer for the following teams right here, only for Pick Your Team form. That break itself will be coming up in a separate video. There's the rules right there. Big thanks to these folks. Congrats to the winners right here and thank you to the people who bought spots straight up. There are the numbers right there. Let's roll it. Let's randomize it two and a three, five times for each list. One, two, three, four, and fifth and final time. After five, we've got Brandon down to Oliver and two and a three, five times for the numbers. One, two, three, four, and fifth and final time. After five, we've got eight down to six. No, I don't need to copy the IP address. There you go. All right. So Brandon with eight, Scott with seven, Brandon with nine, Kyle with three, Robert with two, Anthony with four, Matthew with five, Robert with one, Julie with zero. So again, Julie, zero gets you any and all redemptions for those teams down there in the bottom tab, including one-of-one redemptions, but Robert will still get live one-of-ones. Oliver, you have number six. Let's order these numerically and there you go. Coming up in a separate video will be the break itself, jaspyscasebreaks.com. Bye-bye.


That's how the game goes You have to make money over time to keep your money I'm gonna tell you a hard fact ladies and gentlemen if you want to keep your money You're gonna have to make it over time because money flows not downhill like water money flows uphill It doesn't flow to the lowest common denominator It flows to that place that is hardest to reach as Elon Musk says you get paid in proportion to the difficulty of problems you solve


So now we're gonna share a song from Brazil and kind of it seems like we give more value when we leave where we come from or our origins and I don't think this is necessary you know so hug our culture like the Maori and so this is bossa nova is a music from Tom Jobim it's called happiness a felicidade