Oh my god. This is such a pain in the ass You can tell a good gym from a bad gym by how bad this is All right, check this out I know the gym that you go to has rules on the contract But there are unwritten rules that are true for every single gym and today we're gonna teach you all of those rules You're welcome. We need to remind everybody get out of the gyms are packed again Yeah, you know, it's funny because you don't see a lot of these rules written anywhere But if you work out in gyms long enough or you manage gyms like we did these are real rules It's like what do you call it Jim etiquette etiquette or Unsaid unspoken rules. Yeah agreements. I mean you have to teach common sense common sense is God It's the thing of the past. Yes. You literally have to like explain why now Yes And a lot of these I've had to actually talk to members about in the gym It's not all of them some of them you really want to approach someone talk to about yeah, but a lot of them So let's start with the first one which sounds obvious, but which you would think oh, this is super obvious But apparently it's not because this always happens. Mm-hmm. Don't be smelly. Yeah, don't be smelly when you go to the gym So my first one of my first clients that I ever inherited Was this guy who didn't wear deodorant and it was part of his his culture or not to mm-hmm and he was adamant about it now He smelt so bad that when I would come in for our session like to walk in the front This was capital McKee days when I'd walk into the gym. I would know he was there Whoa, yeah, I know like this brand. No, it was that it was so but like we and so many members complained about it, too It was like we would we and I had to train him so I'm like spotting him and right on anything It was so did you say anything? No, I was so young, dude. I was only this is like you know We're gonna train outside from now on. It's really good for you No, I didn't even have access to do that where what I did do is that if you've been to Calvin McKee Right before you get to back to the bathrooms all the way in the back There's this long hallway and we would go in there and just I would train by myself there So I'd suffer for the entire hour. Did you try to hug you when you say bye? No No, we had we had this one member You guys probably know him because we all worked in the same gym not at the same time But this guy was a longtime member and he would he would get on the stair master It's all he ever did and he put towels on the floor all around him And he would sweat and he wore the same workout clothes every time and I know he didn't wash them Because he would smell so bad and he'd go in there and he'd do his cardio and I actually had to talk to him I actually took him aside and I said hey, man I'm not gonna say his name because I knew his name, but I'm say hey listen Yeah, I love that you're consistent. We value you quite a bit you come in you work out all time You know your great guy and everything but I said this is really embarrassing for me to you say to you But you're you smell offensive and yeah, so you know, it's a hard conversation really hard conversation Yeah, I avoided that a few times as working with clients and at the gym, but I Remember taking this guy aside and telling him when I was just a member of a gym Which this guy was always wearing tank top and would always do pull-ups I'm like could you not pick a worse exercise and the worst outfit Highlight your body odor and offend everybody in here And like I actually like because it happened multiple times like first two I let it slide and then I actually had deodorant in in my bag in the locker room So I went and grabbed that and I handed it to him. I didn't say anything and the guy was like confused I'm like, please use this. Oh, wow. We we Spray deodorant under a guy's arms and shoulder press one time. Yeah, cuz he was it was really bad Bad management on my part. I was young I was 19 years old as a kid and we told him and didn't matter He's it and so I had my trainer go up to him. I said just when he does a press just underneath. Oh my god And yeah, yeah, don't do that. No, don't do that. But anyway, I'll be aware. Yeah, be aware And here's one of the common ones that I think even Somebody who has good hygiene doesn't realize this happens is gloves get stinky. Yeah Really bad.  Yeah, pay attention to that if you wear there's nothing more embarrassing than wearing gloves We're gonna work out except that the glove smell More All right, so here's the next one and this one is Interesting and I don't know if this happens in the women's locker room because I've never been in the women's locker room But this happens men's locker room a lot especially when I used to manage gyms Members would come up to me on the workout floor sometimes But never would members come up to me and talk to me more than when they were in the locker room naked I don't know what it was I'd be in there just doing my walk-through and dude comes up and by the way old men do this It's an old man thing and this is what they do old men will put their shirt on put their socks on Everything except for the bottom half of there's whatever and so they walk up to me And I mean it's it's a t-shirt so it's kind of barely covering things just you know stuff hanging out like hey cells going on Hey, so what about the pools? Is that gonna get fixed soon or what's going on with that machine or you know Woods the other day and it's just like you know just wafted in front of me super uncomfortable I don't think it's appropriate to walk up to anybody and talk to him while you're naked, but don't do it at the gym I'm convinced that's it. It's an it's an alpha thing It's like It's always the old guy not young teenage boys do that like it's like our young guys even do that It's like an old man thing. It's like yeah, I'm on the I'm the old gorilla in here Totally that what an album even even do like the stances even put like one leg up on the yeah So how you doing Sal? Yeah, and you just like I showed him. Yeah Wow, I didn't think I'm convinced that's what I don't know if I'm old enough to pull that yet I'm gonna try that Dude, I had a old guy one time trying to ask me all this like training advice He's like butt naked and he was just like yeah, so I go third your clients and can you show me this? I'm like, I'll show you another time. Yeah, I'll show you out there on the floor I think like he was like trying to get me to to break it down in there I had a member one time and I just I told him like don't what are you doing?  Oh my bad It's this this same guy by the way to the same guy Drizes junk off in the air dryer. Yeah, or the air blower. What do you call it? That this is like international I don't know. Yeah, the air is now circulating in the air. That's now been blown off. Yeah your balls Yeah, that's not that's not cool. And I mean granted. They're probably clean because they just came out of the shower But it's still weird. I don't care.  So they have to get weird positions to drive themselves anyway. Yeah, so it's kind of weird all right this next one this one's a little bit more important and a lot of people don't realize this unwritten rule and there's a Couple parts to it. So we'll start with the first part, which is if you're working on a gym, especially if it's busy Let people work in okay? So if you're on a machine or you're doing squats or bench press or whatever and somebody's like waiting or wants to whatever Allow them to work in so while you're resting they do a set now. Here's the kick Here's the the key to it Whoever's working in if you started the set and you're the first one to use that machine or that that piece of equipment The person working in is responsible for taking the weight off and putting it back on or changing the weight or the adjustment and putting it back On that's their responsibility. So that's the other part of it, but let people work in I think it's so It's such bad etiquette to do five sets on a machine have someone wait and to not allow them to do a set while you rest And do nothing because you see these guys now, especially with cell phones people are texting in between sets And it's like dude. I want to use that machine. Let me let me come in. Yeah, you're wasting everybody's time I mean, it's that's just the thing. I think not a lot of people know about that. They don't and most people don't know Yeah, it's even asked for that. And I think that's something that needs to be expressed You know to new members, especially like hey it because it is frustrating Especially go and peak hours all of your plans for like machines a lot of times that gets interrupted because you know people will Be like that they'll be on their phone in between every set They'll be doing five six, you know seven sets of the same thing and you're like What is this person never gonna stop it? But you can ask politely like hey, man. Can I can I work in? Well, I feel bad for the beginner that Duck one doesn't know that or two is relatively new and then had a bad experience asking somebody the first time So then they just assume some people are dicks about it Yeah, I know there's people and that's the point of this like episode right is to tell this really does be speaking to The dicks more than it is to be talking to the people that should know like, you know By the way, you should be able to do this.  I got ego checked hard with this once like hard I was maybe 15 or six probably 16 And I'm doing squats and a woman came up to me and said do you mind if I work in and I said yeah Absolutely, and I go to take the weight off because no no leave it on and she does more reps than me I remember being I was such an ego check as a teenage boy that this woman could you know And she was built she'd been working out for a long time But still you know your guy and your ego is sensitive right especially at that age But it was but I let her work in or whatever she ended up becoming cool And we end up you know being friends or whatever So I do think there's a little bit of a gray area here or I think an area where we can elaborate I think for a certain like if you I Even though it's okay. I still think that you should be mindful of something like that Yeah, I mean that ended up working out in the opposite change the way Yeah, but like so if you are a 17 year old kid and you squat 135 and the powerlifter in the gym is moving 450 and you want to come in and you want to work in with him You better move the weights fat you better take the weights off and put them on fast It's not very realistic right to move 450 pounds off a bar and I'm not right So be mindful of who you go working and then how much you plan to change what like if you get into a Fixed hoist shoulder-press machine that has literally like you know like a pin and like a seat adjustment That's not a big deal But if you get into like maybe even like a free motion machine that moves arms all different directions and you're you're changing all the settings Or you use a cable machine and someone's pulling it from the bottom And now you want to move it up and change weight like be mindful of like you what you're doing and like how the time in Between rest periods that someone's rest periods may only be one minute long Maybe even a little less and now you're working in and you're completely changing the way down I'm glad you said that it's the responsibility of the person working in to match the rest periods of the person that they jump into Yeah number one number two It's your responsibility to put the weight back and the adjustments back to where they were before and if it's not feasible Like if I'm doing a 500 pound deadlift and someone wants to jump in and put 135 on right probably not feasible unless you can Hustle your ass wait you cannot you cannot think about that Strip and put on back. Okay, they're gonna break it down. Ask me to help you by the way No, I usually will yeah, I'm cool, but that's when you work in you're assuming that responsibility And to my point I think that there's there's an etiquette point there on that person's right right so so good Gym etiquette is that you should allow people to work in well the person who's asking to work in should also be mindful of What you are about to go use of theirs like you shouldn't or like taking like it Someone's using a easy curl bar and they're doing school questions You want to strip it all down and use it for something else like, you know Be mindful of what if you're if someone's doing the exact exercise you want to do and they're relatively close I don't have to be that close but relatively close to the weight and how you're gonna use it like okay That's fine But if you're gonna take the equipment or take the machine and completely manipulated or change it and your eyes His weight discrepancy is huge. You gotta be mindful of that.  Exactly. Exactly. I mean squat racks are common too though because there's there's minimal squat Starting to become you're right. Yeah, it wasn't like you should not be that way before That's why I wanted to bring up the squatting and deadlifting thing because it has become popular that I mean at least my last years of Being in the gym Many times if I came in there at a popular time I'd and this was back at Gold's that had five platforms and five squat racks And I know that I'm deadlifting or squatting is my first thing and I walk in and they're all taken So I would have to you know, and what I would always do is I would look and see Who's doing what and who is probably gonna be moving similar weight to me? And that would be the person or so who I think is maybe on maybe their last set I might walk up and be like hey How many more sets do you have left and if they only got one or two more sets? Maybe I'll wait and then you know Maybe I'll go warm up a little bit and then I'll go jump over right now Here's a here's one that is often written on the wall of a gym And it's this is more of a known rule and yet people still don't do it Yo, what's up everybody? Do you want to get strong? 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That's on sale maps suspension It's a suspension trainer program all you need are suspension trainers and you can train your entire body great program That's also 50% off here's how you can sign up go to maps fitness products calm and then use the code July 50 for the 50% off discount.   Yeah do the work and and put it back. I remember, uh, I'll never forget doing this This was this was pretty epic.   He takes the caution tape and he cautions off the entire weight room and gets on the loudspeaker and clear Everybody clear out of the weight room.  I was like, oh I tell you what but made a huge difference because then you started to see the other members Managing the members they would watch somebody else.  They'd leave it for the staff It's a culture because some k here's and by the way part of this problem And part of the reason why that's good to do this episode is that Some of some members actually think that's the job of the people that work there Their job is to re-rack the weights because they see trainers and people in uniform I've never been to a gym where that's the job of the staff It isn't the job of staff and but k remember We just you just recently talked in an episode about a guy who was increasing the weight on the Gravitron thinking that he was getting stronger because it was helping him more, right? People are that clueless That they assume. Oh these people are on the clock. They have their uniforms are they're floating right?    Yeah, because a good gym culture which by the way this can exist in a hardcore gym You can have a good culture in a commercial gym It's all about the way the staff creates the culture and what they enforce and then and the members themselves If I walk in and I see equipment all over the place I know it's a crappy culture and I probably am not going to like working out there And that's one really easy sign is how much of the members respect the gym That they're working out. That's a really good point because it is it's a sign of reader It's a lot a sign of leadership in there Somebody has built that culture that is taught not only the staff That they all help and pick up and then that's bled into the members that are in there It's a really good sign of a good gym. Yeah, you'll see trainers leave equipment out in gyms like that Yeah, you know, which is oh my god. If you were a trainer you work for me. You left equipment out You're fired right away. All right. So here's another one which sounds obvious But I remember at one point when I was managing gyms for 24 fitness way back in the day So we're looking at I don't know 1999 maybe 2000 This became it's such an issue That we actually developed a rule around it. Um, and and this is the rule that is uh, you need to wipe up your sweat After you're done using a piece of equipment sounds obvious Okay, but it got so bad at one point that 24 our fitness at back then Passed a rule and they said you must have a workout towel with you when you work out If you do not have a workout towel, you're not allowed to work out So either you have one or you buy one at the front desk now. I remember when this rule took place We actually got a lot of conflict from members where people would walk in. Where's your towel, sir I don't have one.   I I actually was a part of the transition of the the before and after also. I was there early years in fact um One of the things like signature like looks that I had was I wore a towel like almost like a quarterback did over and and I started doing that because I had clients and that would became it like even my own clients were being paid and I'm telling would forget Because I was during the time of before and after like when nobody was told to do that And then all of a sudden we're telling the people that so I began to carry the towel myself So in case they forgot I would wipe it up and that's how that started But that was a hard transition to get people to remember that. Yeah. Oh, yeah because people again The culture was one way she was going to get cleaned up behind that and members assume that if you wanted that done Then you provide a towel service But what you don't realize is you're paying such a low membership fee for a gym like a 24 fitness This is not a spa you go to a spa like you were going to club one They provide the time and they have a laundry service and that's expensive to maintain that extremely Yeah, you're not you're not getting a 19 to 19 dollar a month membership and getting a towel you'll pay 10 times as much Yeah for that Yeah, so you're not so you got to understand that if you're paying that low in a gym because that's the other thing too You get asshole members who expect that they think that like oh, I have this membership I pay for this membership. You should provide that stuff It's like that's why you pay 19 dollars and you don't pay 120 dollars to go to like a club You know a club whatever club or a club sport that is like a you know a spa where they do that Now I do think that this has become much more of an issue after the after covet I think now all gyms are like really big about it and members are too I see people now more than ever Well, most spraying equipment down and cleaning after the dumb so most gyms now how and most your commercial gyms Have if you don't provide a towel service You've now put the towels and a spray bottle in stations all over the or dispensers of like Those wipes or whatever. I've seen that too.  All right, so here's another one that Isn't 100 across the border rule. There are exceptions, but we'll explain them here in a second Which is don't drop your weights on the floor when you don't working out with them And I I would always tease members who did this and say if you're you're not strong enough to lower the weight properly Then you shouldn't be lifting that much Throwing weights on the floor is not only dangerous. It's also lazy Um, and it's also not respecting the equipment like I wouldn't throw Uh, you know, lots of pieces of equipment down on the floor for potentially damaging the equipment now Here's the exceptions. You're working out on a, you know, a weightlifting platform platform That's the only place that's the only that's where you're supposed to drop the platform. Yeah, that's it That's it. I mean to me. That's that's it's an easy thing to know where you can and you can't If you're on a weightlifting platform, it's designed for take that, you know, I saw somebody actually, uh, Yeah, breakages the floor somebody actually broke someone else's foot and one of the gyms I managed Yeah, dropping like 120 pound dumbbells, you know, flips and rolls. It's common on the bench press.  There's a way by the way because I get this if you're handling really heavy weights It's like it's really hard to lower them super slow But there's a way to let them fall Where it's still under your control and then there's the way where people literally guided at least Yes, but they literally drop them and they end up flipping and rolling a couple times, which you hurt somebody that way Yeah, and I also think that if you if you're Lifting dumbbells so heavy that you can't you can't get it back up to get on your knees and then roll out of it Like you don't you don't belong lifting that weight yet, dude. Yeah.  You got to be considerate of everybody else That's just I mean, I've seen I've actually seen dumbbells break from people dropping them from dumbbell pressing Yeah, like a heavy 120s like that and it just it hit just right and wrong and that's so much weight It's snap that snap I remember back in the day when I used to deadlift back when deadlifts were not popular So this is when I was the only one ever deadlifting in the gym and the plates that we had Were those stupid hexagonals Which I that's the worst place to deadlift with because you put it down the floor and it shifts the weight And then you got to readjust or whatever and um, I mean I you know now I use bumper plates so I can drop the weight if I need to but I would put them down carefully Because especially if I drop one of those because of the shape of the plates It would shift or twist and I would hurt myself if I wasn't careful Well, yeah, I mean even like to your point with the dumbbells like slam and down I remember it loosened it up to where the next member use it and like it came apart while they're lifting the weight So you just set somebody else up. Yeah for potential injury.  All right. Here's another one. I Hate this one. Sometimes it still happens to me Don't talk to people mid-set If they're in the middle of an exercise Don't approach them and start they're con you need to concentrate and focus on what you're doing And I've had people Do this to me where I'm in the middle of a set and someone starts talking to me and I've literally said shut up Like just look straight in shut up because it's it's distracting and to me. It's strange What makes you think it's a good idea to talk to someone when they're working while they're in the middle of work This is a tough one because it's it's uh, it's less of a gym etiquette thing And it's more of a self and social awareness thing This is like the same person who's like the close talker or the same person Doesn't get the sign that you're not wanted to be here right now Like it's that it's that same person like pick up on it Because yeah, because I feel like before you even say something like shut up or you become an asshole Like your body language is already telling you. You're not interested in talking to me. I'm talking to you You're not even looking at me anymore.   Oh, yeah Like hey, so how's your weekend? I just had dental work done not that long ago And I it's so funny you bring that up because I was thinking the same thing too Why are you asking me questions and and then two like you'll ask me a question And then like two seconds later be hold on hold on and then she'll be doing something I'm like you just asked me something. It has to be all rhetorical questions. Yes. You just answer your own I just answer like hey, hey I though I love it. All right. Here's another one. Uh, we just talked. I mean the first one was don't be smelly This is part of it. Don't wear a lot of perfume or cologne When you're working out. This is super annoying. It gives people headaches. It makes me nauseous. Um, so I'm gonna I'm gonna add to that that's like I don't know if this falls under genetic it or it's just like and So I think there's like Getting ready like and this happens a lot like you see girls guys do too though guys and girls both do but girls So you see Obnoxious cologne when you're when you or when you put on makeup to go to the gym Like you put on like a bunch of makeup. I understand you if you came straight from work That's totally different right coming from work and you worked all day Oh, you could tell people get ready for the gym.  I'm sure she's come straight from work before But then there's like the the girl who consistently comes and who is completely made up as there is the guy Who does the same thing who gets his hair all done like all nice and he's got his outfit that matches And it's perfect and stuff like that and I get you feel good. You look good I get that whole that whole thing But there's a point to that where I think it's a little ridiculous when you're putting on Cologne and perfume and you think you're going to the nightclub versus one of the I would rather I'm going to say a controversial statement I would rather work out next someone next to someone with like moderate BO than strong cologne or perfume the cologne or perfume makes me nauseous Well, I would agree with that because I'm really dizzy and nauseous. Yeah, I'd agree with that And so yeah, don't do that Don't spray like these strong smells on you and then work out because it messes people up to kind of add to that There's also been issues for me as like Some people like bring their lunch In the weight room like the eating in the you get always disgusting. That's like a bodybuilder thing Dude salami and rice.  He's out for that one. I want to slap people Because they don't want to miss the anabolic window. I got my food. Oh, I just finished Let's see my no food in there. Do you get out of here with that? Oh, there was a guy that would when I I worked out for a short period of time at golds the same one you went to adam And there was a dude that tilapia and broccoli. Yeah, I have two worst foods No, I had for I 100 percent my I have some friends that are super guilty of this like because they And they would be in the gym for two and a half three hours.  All right. So this next one, you know, it was always kind of an issue But not a huge issue that crossfit happened. Yes And and all and all of a sudden the bad thing they came for we give them the credit for the squats in the dead List making a popular gift But don't hoard a bunch of equipment and dumbbells and I mean crossfit happened all of a sudden you'd see members with like Six different pieces of equipment and exercise strung together like these are mine I'm doing my giant Handstand walking in your way like dude get out of here.  I'm not going to go be like that's mine Okay, so where this happens and I'm just Okay, this and crossfit is really guilty for a lot of people do this It's not doesn't mean that other people don't too, but they are following a wad And let's say like that wad requires 80 for their strength 80 pound dumbbells and they also have to do pull-ups and deadlifts and some other in a Rower or something like that.  No what I used to do What I always what I used to do is I would see this happen And it was like super sets fine to exercise an open deal and then again If you're going to use multiple machines or exercises leave them where they're at you travel to go get it Yeah, you travel go get it and if someone's using it then you figure it out That's the way I would so that's my point, but the reason why they don't it's because you know crossfits for time That's okay. So you're not they're trying to improve their time And that's how that's why that happened was because it's a time thing and that's wasted time to walk over to the dumbbell So they would want to put it that's okay.   I would go and use whatever you yeah, I'd wait I'd wait Oh, he's about to use it and I go over there and start doing some shrugs Or I'd bring a client over there. We're gonna use this machine today and just wait for them to just get annoyed and be like I please I hate that But that wasn't a thing crossfit happened then it became a big thing for a little while Not so much of a thing and that so under the hoarding equipment is the same category too And the same it's a different type of person, but it's also guilty of like sitting on the machine for, you know 25 30 minutes you've seen that before dude before this again. This was back in the newspaper. Yes Right, this is before like a guy like that before smartphones were a thing There were dudes that used to literally bring newspaper to the gym They would do a set and then they'd read the newspaper in between for like, I mean 10 minutes I had a I had a lady one time that I had us check that used to read romance novels on the lake press That's a real thing I swear to god, dude, she she'd get the leg press She was her fire and we only had like two leg press machines. You know what I'm saying? Of course leg presses is a popular machine It wasn't the one with your picture on it This is before this is before my romance novel days, right? So she would sit there and she would read her romance novel Do a set of leg pressing go back to read a chapter and then go The worst the worst the worst is I would see sometimes people read while doing the exercise I've seen that. I don't understand. The same lady's done that. Yeah, like, how are you able to set work? Yeah, how are you doing leg extensions while you're reading? Are you sure that's enough weight? You might have to add a little weight. You might want to focus a little bit So this last one's kind of funny. It's kind of a joke, but uh, and this may be a personal one I don't think anyone in this room likes this. I don't think it's a joke.  I've seen that before I've had it and I've had members complain like like come to me Moose knuckle and everything. Yeah, it's that it was so fitted and so tight that they're like You have to get this guy out of the gym like this isn't so inappropriate. I can see the vein in his balls Yes, that's exactly how I approached him. I don't want to be able to I don't want to be able to know your religion by looking at your pants Oh my god. Yes, you're circumcised. Yeah Please cover that up. Yeah, and that and that is a hundred percent guy thing It's a guilty guy thing that does that the guy there's a handful of dudes that you'll find in a gym That absolutely do that that will rock those spandex and they're super super tight It's performance enhancement Dude, there was a guy there was a guy that worked that used to work out one of my gyms used to wear a wrestling singlet That's it. So it's like really tight, but just a wrestling singlet. He's just walking like what's going on here, dude? Are you just wrestling? I hate to try to throw that guy out. Yeah He's cool Anyway, there you have it. Look if you like this show head over to mind pump free.com and check out our guides We have guides that can help you with almost any health or fitness goal You can also find all of us on social media So you can find Justin on instagram at mind pump Justin add him on instagram at mind pump adam And you can find me on twitter at mind pump cell How do I Incorporate cardio and not lose muscle seeing people do this before where they'll start to lose the sharpness of their muscles Or they'll start to lose the sculpt a little bit and that's disheartening But if you do it right then you minimize that muscle loss or that metabolism slowdown In fact, if you're right You can actually speed up your metabolism at the same time that you build stamina and endurance You just have to be able to kind of program it Properly and the way to program it improperly is just to go do it as much cardio as you can for as long as you can right


We have one more day until we get to see some more basketball. But, um, that does not mean that the NBA is not still making news because yesterday I'm not going to call it a gift because this guy didn't get a gift. Nate McMillan fired his head coach of the Hawks 29 and 30 right now. They're sitting at eight in the East. I guess the timing, uh, is probably the question here shams or were other times earlier this season specifically that this might have been more sensical? Like why, why now? Well, I think the reason this happened now is they had two really bad losses right before the all-star break to Charlotte and to New York. One of those games, they gave up, I think 144 points. And I think they looked at that as a bad sign going into the second half of the season. And we've been talking about Nate McMillan's future since December. When he had that incident with Trey Young, where Trey Young no showed to a game, um, after his exchange with Nate McMillan at pregame shoot around in December, we've been discussing Nate McMillan's future. And the fact that whether it was in season or in the off season, he was not long for this job. He was going to be fired eventually. And that's when several weeks into December, I reported that he, he attempted to step down as head coach. He wanted to resign from his, his duties. And so that's where the writing was on the wall. He was going to be out after the season anyway. So I think the Hawks preempted it and get it out of the way now, especially after two really bad losses. And so they're going to start a search, they are trying to make a hire in season. And so a few guys will really look at Quinn Snyder, Kenny Atkinson, Charles Lee, Jordy Fernandez. This is a team that's 29 and 30, eighth in the Eastern conference, a lot of turbulence. Travis Schlank goes from president to now basically not in the organization. Nate McMillan goes from head coach, a guy that's on a three or four year extension to not, now he's not a head coach anymore there. So they're shuffling. They've, they've restacked the decks there and we'll see which coach they try to bring in, but I would, I would keep an eye on Quinn Snyder and Charles Lee. And if they're trying to go big game hunting, Quinn Snyder as the best resume and probably the best available candidate of anyone right now. I mean, look, Landry Field, and a lot of these movements were made in December, right? Like a behind the scenes, they're not as sexy. So we probably didn't talk about them as much, but Landry Fields is their GM now that happened in December when, as you mentioned, Travis Schlank slept step down. So things have been happening behind the scenes. Right now Joe Prunty, former Spurs video coordinator is the interim coach. The timing is bizarre Chandler. Obviously they're saying that this is good for the team moving forward, but now we get to discuss whether or not it's good for the team moving forward. We're going to run the floor and I asked you first, Chandler, was this a good decision? I mean, look, it seemed like the writing was on the wall in a situation like this, like Shams just said, but the whole Trey Young incident, he was going to step down. He wanted to leave now. And I do think it's the right decision just because he's going to be gone anyways, right? Not that Nate McMillan deserve to be fired.  I just think that the Hawks made the move for Dejante Murray. They're very underachieving this season so far. They had high expectations and they're battling right now on the eight seed and they have a lot of talent. So I don't, I think they strongly believe that they can make a splash here. They could hire a guy like Quinn Snyder, who's an unbelievable coach and they still have the talent. When you look at their roster with Bogdanovich, Deandre Hunter, John Collins has been on the trading block for about six years and aren't moving him. They have the talent. They have the pieces. They're just not playing well right now and someone's got to be the fall guy. And this is exactly why I would never want to be a coach because it is a tough, what have you done late for me lately? It's not necessarily fair, but at the end of the day, they are underachieving and they're not winning as many games as they expected them to win and that usually falls on the head coach, especially when you have a star player like Trey Young who in the headlines has publicly got into it with him, doesn't go to shoot around or doesn't go to the game. That's all stuff that makes it seem as if Nate McMillan doesn't have a hold on his team, let alone a star player and usually it's going to crack down on him. But I think they have enough talent on this roster to win some games and just a change might be the best thing for them. Ooh Eddie, what do you think? Yeah, it's very interesting the timing of course, but I don't know when else they could have done, I guess maybe Monday, you know, but they didn't blow it up at the trade deadline. They clearly want to make a run this year. They're only a season and a half removed from a conference finals berth. And that was a conference finals berth that they felt they could win. Trey Young got hurt in that series and they were right there. They felt like they could have made a finals run and then who knows. So, you know, they didn't trade John Collins, they didn't trade the 100, they didn't trade Bogdanovitch, all these guys that were rumored for months and months and months and John Collins, everybody had him traded by now. So clearly they feel like they had the talent to make a run and they need a new voice there. What I wonder is how much of this trickles back to Trey Young.  The CEO could deny Soms report all he wants, but here we are a month and a half later and Nate McMillan is no longer the coach of this team. So, you know, when you got a guy who can average 30 points a game and give you 10 assists a night and he's willing to go to the front office and say, Hey, me or him, it's always a dangerous job for a coach. So, you know, I don't know if Trey cares to break that stigma or what, but it's there and it's an interesting time for this franchise because, yes, they didn't blow it up in February. They didn't blow up the trade deadline, but what's to stop them from blowing it up this summer? What's to stop them from calling around and wondering what the price tag is for Trey Young for their new coach, their new GM and a new regime out there in Atlanta as they want to build a new franchise. You know, they're definitely a team to watch. I got Trey high atop my disgruntled stars list. When you look at all those teams that are gathering five, six, seven draft picks and wondering what they can turn it into, it might be a Trey Young. You might be able to turn that into a Trey Young this summer. Yeah. Look, you never want to get that coach killer, you know, reputation. And I can speak for the first time. The first one was not Trey Young's fault. I was there in Atlanta. Lloyd Pierce was not a good fit. He was not a cool dude. He was not a great dude. He wasn't a great coach in my opinion. He was my least favorite coach I've ever played for, to be honest with you. And so that wasn't Trey Young. Yes, they butted heads, but Lloyd did not know how to manage the young talent. He didn't know how to manage Trey Young kind of becoming the star player that he kind of went rogue there. And in my opinion, deserve to get fired. Nate McMillan is another story. I haven't heard nothing but great things about them. Obviously I was in Atlanta, so I have my own personal experience. This is different. And again, Trey Young is a scoring, you know, point guard that's young and he's not the most mature leader on a team, right? And so I think the best thing for Trey Young is for them to bring in a star that kind of relieves him from being that guy because I think his best asset is facilitating the ball. He's got a great vision. He's always going to be able to score points. He's always going to be able to shoot the ball from extremely deep. But I just think the more he grows and the more he matures as a player, I think he's better off as a two or three option than being the main guy because this isn't good for him because now this is, this is the second coach and this is the GM. And now he's got, you know, it's just, it's not a good look, whether it's his fault or not. And as much as things fall on the head coach, I could have said, a lot of the falls on the star player. And this is Trey Young's organization. They gave him the contract. They drafted him. They traded him for Luca Donkens on draft night like this. He's got the keys. And the cars not really anywhere. So they had the great year where they advanced in the playoffs last year. They made the big trade this year and now they're kind of underachieving and they're in panic mode, but I'm not giving up on them quite yet. I still think they have talent and I do think Trey is a star and he has the chance to kind of get over this hump of this reputation of being a coach killer because the first one wasn't his fault. Yeah. I mean, I think with Trey Young, it's a tough situation because they were going to fire name McMillan regardless of whether whatever happened with Trey Young. And so the writing was on the wall, but for Trey Young to put himself in that situation where he was combative with the head coach and decided not to show up to the game. And I think that's where the organization from what I'm told over the last 24 to 48 hours, they just came to the conclusion that the players had fully tuned out Nate McMillan. They did not feel like Nate McMillan had a pulse on this team anymore. That his time was over. And so it was really just ripping the bandaid off. And that's exactly what they did. I mean, good Lord. It was like a season and a half, two seasons ago, he was the savior. They were in the garden. They were like America's sweetheart team. And he's talking smack to everybody. It's crazy how quickly everything can turn. Obviously now the search for a new coach goes on. As of right now, whether they trade him or not, Eddie, which that has validity to it as far as what you were saying, but it's his team. So Chandler, how much input do you give a Trey Young when you start looking at the names you're seeing on the screen right now for potential new coaches? I think you bounce some ideas off him. And Landry Fields was a player. He understands that you need to make a guy like Trey Young.  They need to make them happy. They need to make them comfortable with this decision because they have to vibe. They have to get along. And if Trey's not going to get traded and he's going to be there, he's the main part of the success of their future with this new coach. So I definitely think that you're going to go to him and ask him and, you know, have an opinion. Is it going to be the final say? I don't think Trey has that kind of juice. And I think everything that's led up to this moment, it has kind of lessened for Trey Young to where he'll still have a voice and have an opinion, but I don't think it's going to be like a, you know, a Luca Donkitz juice anymore that he would have or someone like that because of the history, because of the two coaches, because of Travis stepping down. A lot of the media scrutiny has fallen on Trey. And so I definitely think they'll make him as comfortable as possible, but they're not just higher on who Trey Young wants at this point. I don't think so. So I have a, I have a proposition for Eddie, but before just, that's, that's a tease because I want you to get really excited mentally inside. Before that though, I have a quick question because it seems that across the board, and we saw the George Carl tweet earlier that it's a, it's a me league versus a we league, right? It's Donchich versus, or it's Yokic versus Trey, that kind of mentality. A lot of people love Nate McMillan. Like I've heard nothing but positive things. If you're an up and coming coach or one of these guys on the list, do you take that into consideration if offered this job? Or is the ego of a coach such that you think it's not going to affect me? Chandler, what do you think? Like, is that, you know, coach is more than most like it does. Do they even take that into consideration? Yeah. If I'm a young dude, like Lee from the Warriors, and I actually have an opportunity to get a, you know, three to five year deal. And, and with all this history of Trey Young, it's almost like Trey Young is like hiring Irving now where he's got to behave. He cannot have another coach. They can hire a young guy. And I think before they fire the next coach, I think they would trade Trey Young. So yeah, I would take it.  I'm definitely take it because I firmly believe like strike three and whether it's Trey's fault or not, I think the next coach they hire, that's who they're going to, that's who they're going to roll with with this roster. And whether they make a move or not for Trey, that that's up to him and how he messes with whoever they hire. It's the eye can change him. I love it. Okay, Eddie, the movie Eddie, this is the scenario I present you with. You are offered the moment. You want to coach the Hawks or what? Yeah, I coach the team that the White Howard plays for in China. What do you talk about? Of course I coach the Hawks. You know, this is a team with talent. This is a team with a style of play that is shown and has worked and two young all stars who we know our talents in the league and one of the most important positions. So it's it's absolutely enticing job. And especially if you can build that relationship with Trey and go from there.  I think it's, you know, probably the best job available right now. Right, fair enough.


Hello everyone, welcome back to the session of Data Different Decision Making and Essentials of Predictive Analytics. In the previous session, we have discussed different type of business analytics or say data analytics and then the steps of data different decision making. We discussed the descriptive analytics, the predictive analytics and the prescriptive analytics also. We also discussed that what are the essential ingredients or the techniques that you need to know to understand or to become an expert on the data different decision making domain and also we have discussed to some extent different requirements for descriptive analytics, predictive analytics and prescriptive analytics. We have also discussed the data different decision making process like business understanding, data collection and pre-processing, model building, model evaluation, model development, model maintenance, etc. We have discussed detail of business understanding with different steps and the requirements and also to some extent essential of predictive analytics also to some extent we have discussed. Now we will be entering more of or to some extent in depth of data, pre-processing and the collection of data types so that you can enter into the model building on what are the techniques available for model building process of especially the predictive analytics models. Then model evaluation requirement and model maintenance part we cover. Now let us come to the data collection and the pre-processing process. Generally you know in when it comes to the data collection you need to think about the data source, the reliability, the consistency of the data, the accuracy of the data and like you know to some extent biasness or outlayer you have to think all these things. So reliability and the source of data and the data consistency is extremely important before you make any informed decision by analyzing the past data. So therefore accuracy or ensuring the accuracy of the data, completeness of the data if the data are not available I can give you many such examples where we fail to develop some new innovative models because of the non-availability of the data or reliability of the data. I will give examples in some session you will get to know like you know in India there are many government sources or you know many you know practical platforms where data are not completely available or completeness of the data are not been there. Therefore if you want to do some any project or some you know some research activities what happens you know you might not rely on that particular data and hence you will fail to not make better informed decision based on the data available data with you. So therefore you need complete data, reliable data and consistent data so that you can make a better accurate forecast or you can say you know predictive or prescriptive decision making or business analytics modeling. Then the quality of the data are also very important you might have the available data or reliable data but the data which actually make help you take a better decision or you know to some extent you know improve the accuracy of your predictions may not be that quality of data is also available. So you have to think about the quality of data there might be very data which are very vague or to some sort of fuzzy type data which may not be suitable for your decision making. So therefore you have to think about the quality of the data also. Also when it comes to the source of data make sure whether data are continuous data or discrete data whether it is a qualitative data or quantitative data we have a session inter session on this particular slide itself like you know type of data and the you know different type of modeling process of data type also. Inter session are been you know been allotted for this particular information that understanding the data type and you know what type of you know modeling approach you can you know apply for different data pattern that also we will discuss but here I am giving a summary as a part of introductory session of essentials of predictive analytics. You can think about whether the data are qualitative data or not quantitative data or not. If the data is a qualitative what kind of you know subjective approach you need to follow. If the data are qualitative what kind of group decision making approach you need to follow if the data are quantitative in that case what kind of regression analysis or what kind of causal models or say time series models you need to use that also you need to understand and accordingly data patterns understanding reliability consistency data you need to understand. And corresponding model you have to bring of typical quantitative analytics of quantitative modeling approach. Then whether data are structured or not unstructured or not that is also very important in terms of text mining or the machine learning process you need to really require whether data are structured or not or unstructured data whether if you have a data of this type how to handle this type of data also you need to understand whether data is a big type or big data type or not. If the data are a big type how to handle all these things you know whether 3 v are involved over there or not data are not in large in volume still you can talk data are a big data also if the variety and the velocity of the data are quite high. And therefore you need to understand the data pattern effectively and the corresponding collection like cross sectional data next slide I will discuss about that cross sectional data time series data panel all these things are very important about the data type. Once you know that then you know you need to think about you know data collection process also like whether the primary it is a data you need to collect through primary sources or you need to collect the data from the secondary sources. Then the major important part you know that ethical consideration you cannot data collect the data which are not been allowed to you know take without permission from the organization. So, you need the ethical permission you need the safety that safety you have to provide that you know declaration to the organization that you know you will maintain you will not use for commercial purpose or whatever the region it is been given to you you have to you have to maintain that protocol guidelines safety of the data and the privacy of the data you have to maintain the legal compilances are also very important to during data collection process that especially the ethical consideration. You have to you know declare the ethical parts about the data collection and the you know maintaining the privacy of the data. So, these are the you know couple of important aspects that you know before you enter into the data collection process for any research or any study you have to maintain this particular couple of aspects of data type and the data collection process. Then I was talking about primary data and the secondary data. You know more detail we will discuss in the data type session or type of business forecasting session. So, but here as a summary let me share that two type of data collection process one is the primary data collection or the primary type of data and the secondary type of data. There are two major aspects of data type and the data collection process one is the primary that is called you know through survey through focused group interview process or you know data collection through Google's seed or so you know through social media network you can collect the data through alumni network also you can collect you can directly visit to the consumers you know stores and you can take the opinion you can directly visit to if it is a manufacturing related projects to you have to collect you have to visit to the you know manufacturing plant and you have to take the opinion of the managers the labor etc. Then only you will be able to take a decision over there. So, all this may fall under the primary data collection or through survey process you know you can contact the interview also for qualitative analysis there are very good techniques involved through you know like you know institutional theory, stakeholder theory through that you can also you know do some primary data analysis also collect the data through interview process you can do the sentiment analysis also of the interview and then extract the data through any software there are many you know techniques are there and then you can take a informed decision through data analytics techniques. So, this type of process you know social media monitoring also through that also you can do there are many marketing agency available in the market through them also you can collect the data whether from the top manager managers opinion you can also take you can take the you know direct consumers opinion also all these things fall under the primary data collection through what about the way you follow like for example here I have given an example that if you want to identify the significant factors that you know impact the last mail delivery of say you know any supply chain or the e-commerce domain in that case what are the important factors that you want to study what you have to do you have to create questionaries by literature survey you can identify the factors and then you have to validate that for the expert opinion right who are working on the last mile domain of supply chain or say you know e-commerce domain so that take their opinion and then you you know clear create your Google seed or you know direct interview and that survey process fall under primary data collections but when it come to the secondary data collection for the same problem I talked about you know say last mile delivery etc in that case suppose if you think about the e-commerce domain same domain I have kept as examples here you can see it's a secondary data so data secondary data says that data which are been stored or been you know be developed or the decoded by someone else when you collect that data from someone else through secondary person so we call it as a secondary data or like you know public or existing information collected by others you are taking that data and you are analyzing that called secondary data you know you go to Demat store say every day huge amount of data been stored right in Amazon every day you are giving order every people are making order through Amazon say or say you know Flipkart etc or then then all the data are been stored over there so you are not collecting that data they are collecting that data and you are collect taking that data from their sources through their SQL database or you know DBMS database and then you are making your decision making through data analytics steps techniques predictive analyzing modeling so that data source of data or that the collection of that process fall under the secondary data analysis or secondary data collection process it can be in a company websites it can be government of statistics it can be in a industry associations you know publicly available market research report or you know different database sources also the example that I was talking about last last mile delivery in that case suppose you want to see that how many products are returned by the consumer suppose consumer give the order and they keep the product in their cart or say you know cancel the product even after delivery also in that case how many product are getting cancelled that actually hinder the business of the e-commerce firms so in that case in the last mile if they want to focus that how I can improve my cancellation for the consumers or how can improve the customer satisfaction or hit rate in a better manner so in that case you do not require to some extent the primary data analysis you need to see the data pattern the consumer behavior of your data how they are which product they are canceling why they are canceling all this you know like you know in which day they are canceling the reasons of cancellation suppose or return of the product you might get to know once you store the data of secondary analysis entire product characteristics consumer behavior etc you can study based on the secondary data analysis that falls under you know second category called the secondary you know data so there are two major category one is the primary data analysis or primary data collection process the secondary data analysis or the secondary data collection process then all this I am talking about the data source data type and the data collection process right now if you think about the data type here I have listed you all are aware about all these things but I have you know categorically mentioned all this type look at the examples and the type of mean analysis like regression time series analysis which we will discuss in detail we will get to know then the categorical like you know data say you know red female you know male etc blue etc different type of product in orange apple this type of categorical if you define that then what kind of method you can follow national learning techniques you can follow whether it is a logistic regression or the classification of the decision tree analysis you can follow that look at the ordinal number you know small medium large category and then rank order analysis you can use look at the binary data yes no kind of thing whether you know the product will be like insurance will be provided or not loan will be given or not so in that case you can take a decision by yes no kind of thing to false kind of decision logistic regression of hypothesis testing can also follow contextual data like you know text mining you can do like you know how hello how are you different like people are you know suppose something some movie are getting you know popularity in the market so people are tweeting on that or people are putting comment on the social media so if you take that social media data and then if you do mining over there and you get sentiment over that the customer sentiment etc on the data then you can follow some text modeling approach also no then you can think about say spatial data so in that case you know you can use GPS coordination you know also you know like in a map type of examples in that case you can use GIS technology think about you know time series analysis time see if the data you have time series temperature also in stock price etc you can use forecasting on the trend analysis image also here I just talked about you know you can use about so much photography extra images etc in that case if you have a that type of data you can use image recognition or you know computer vision all these things processes network analysis if the data is of that type like you know draft theory techniques or you know network analysis you can use also audio type data also you know in that case in a music is speech recording also like you know if you do a primary interview with the data with the experts so in that case you know your data might be an audio type right so in that case you can use some speech recognition software audio signal processing like I was talking about in the software through that you know you can extract the speech recognition through quality forecasting methods or quality to you know analytics methods so these are the different type of you know data and couple of examples I have mentioned and also some techniques I have mentioned for you whenever you required all these things type of data and which techniques to use you can refer this particular slide and you can you know think about understanding the methodology of the techniques and you can implement that particular analytical models or the data analytics techniques then next part which are very relevant to our courses of business forecasting that is called whether the data are of stationary or non-stationary data I repeat all these I will be discussing detail in data type session but here let me give a summary of definition these two station of what is the difference between stationary and data analysis non-stationary data they are very crucial if the data are of steady over a period of time or you know variation are not been there involved over period of time like you know mean variance and the standard emission of the data I will not change much that I will show you in the next slide in the graph so that type of data are called as a stationary data and it is easy to make a forecast for the future but if the data of non-stationary that means it is too much of jigsaw variation or randomness are involved over there so in that case you know your mean of the data for a different block or different time period will shift so if the mean on the variance etc changes over a period of time in that case that data are not stationary we call them as a non- stationary data it is very difficult if the data might have up or train down train and then again down train up train etc seasonality also many factors can involved over the data random behavior like you know behavior can also come to the data in that case it is not easy to make the forecast for future because what has happened that may not be followed in the future so in that case how to make the forecast so that type of data analysis is very crucial for you know business forecasting for the time series analysis we call them as a non-stationary data here one is a small example that I have mentioned look at this data are called as a stationary data because any block of the data over a period of time if you take you know what happens you know the mean of the data remains same almost it remains same it not changing much mean variation so the data remain inside a you know you know range or you can say inside a you know band line so it is very easy to make a forecast for the future also but look at this data the mean may be here but once you shift the block from this location this time period to that time period you can see the mean has shifted so to some extent there is a big gap in data pattern in later in mind go up go down you know so in that case it is very difficult to make the forecast for the future so how to confirm non-stationary data into stationary and make a informed decision will study that through different modules of you know business forecasting then you know another concept also you should know that is called the whether the data of time series data or the cross-sectional data if data are been collected you know at a same time period for different location for different variables that type of data are called the cross-sectional data but you collected the data for a same time period look at that you know cross-sectional data consist of observation of many subjects at the same point of time but when you talk about the time series data use you stick to a particular parameter particular variables and then you collect the data over a period of time over a period of time you collect the data for that particular variables and the way then you analyze that data for you know future analysis or the future predictions so that data are called the time series data which are been recorded or the collected maybe primary or secondary process whatever the collection process you follow but will be collected over a period of time that is called the time series data but cross-sectional data are at the same time period look at on the other hand cross-sectional data focus on the several variables at the same point of time so same like today suppose you want to collect the data say temperature or say humidity or wind speed of Delhi, Bombay and say you know Calcutta, Mangalore, Chennai at same time period you check what is the temperature there what is the air quality etc you check and then you make a decision over there that type of you know you can do many analysis also like social analysis also social science project you can take and you can do analysis over there for different city demographic analysis also you can do that type of data may follow under cross-sectional data so you have to be very careful about what type of data you are handling and what kind of you know panel of data you are managing and you are making forecast for the future or analyzing the data through data analytics techniques and tools now let us come to the data pre-processing so here you know remember it once the collection process are done or you know data understanding are been over then you may make sure that data should not have in out layer data there should not be missing data if there is a missing data how to come up with the appropriate replacement of data or how to remove that data that you have to take care also data transpiration you have to do scaling also like you know you can take Laplace methods or you know you can take the logarithm to scale down the data you can reduce the dimension of the data so all this are part of data pre-processing so missing data out layer you know removal of duplicates all this you know string variables analysis all these things comes under the process of data pre-processing which is a part of descriptive analytics or you know exploratory data analysis very crucial this part is that data pre-processing if you are strong enough of handling a school data analysis through different techniques of you know data pre-processing probably you will get a clean data and also you can make a better forecast like you know you can think about say skewness let us think about say you know measure of like it is all about exploratory data analysis right suppose one examples are given here skewness look at here you can think about data this data has a symmetric distribution because the mean median mode are falling in the same point but look at here this data has a little bit of skewness because if you change the data time collection or the you know data variation changes over there so you can see that the mean has been shifted here so therefore it's to some extent positive skewness look at how this data has a negative skewness so means has come down to the negative side or you know you can think about you know this type of data analysis very carefully you have to analyze the data there are software there are techniques the last module of this business analytics session I will show you on software through that you will get to know that different type of data analysis inter-exploit data analysis will get to know it in half an hour so all these you know calculation process or the data pre-processing how we can get to know one at a you know step I'll show you through you know excel at advanced excel software called address software and then you can think about say you know look at the pattern of the data whether you need to read by read multivariate data behavior of pattern here I have shown you on data behavior of pat or say pattern of the data you can think about that red color data which are now the suppose a actual collection of the data or say in a sales of the data but it is following some you know uptrend of the data as well as you also it is following some signality pattern look at the pattern of the data it is following some peak at particular time period of a year particular time period of a year look at here so here you can see this I have already mentioned here you can see all these peaks are nothing but some signal variation it has been repeated every time period but that will follow similarity in the fourth term here so how to make forecast which model to select so all these things are part of you know explorative analysis and the appropriate selection of the model so that look at here randomness randomness is also involved so suppose COVID during COVID there might be cases that where there are no sales stores are closed so in that case this randomness you cannot bring in the next stage here also right your system has come back to the normal situation now so in that case how to analyze this data how to remove this you know outlier or bring the smoothness of the data that cleaning process the explorative data understanding the data pattern and all these things you know are very crucial for prediction modeling or say descriptive modeling so these are the initial part of you know descriptive analytics or the data preprocessing and to some extent data collection and the data modeling part as a part of descriptive analytics or model building process stage 2 of model building process under the data decision making now next step is the look at the first step of data decision making that is called the model building right under model building the major concepts of you know machine learning or the predictive analytics will come even prescriptive analytics will come all these things are part of data decision making the major part they are the model building nothing but are the predictive and the prescriptive analytics under predictive analytics you can think about different type of supervised learning but you know also you know some there are many techniques of model building like you know dimension reduction or you know factor analysis all these things are part of you know network analysis are part of unsupervised learning also look at here I have written couple of steps of you know unsupervised learning there is a session called introduction to machine learning under this business forecasting course I will discuss detail of this particular slide especially this part of you know unsupervised learning and the supervised learning techniques and the application process of that but let us see the summary of this like you know clustering process segmentation k-means clustering you know hierarchical process of data segregation and then in a linear dimension reduction support vector machine you know principal component analysis they are very important for example support you have a many dimension of the data right many variables many parameters other but you cannot handle all them but you might have to take the most appropriate parameters of the data and you can show that you can understand the data pattern and you can make the better forecast for the future in that case you might reduce the dimension of the data through say principal component analysis I can give one example says for example say suppose you have a say logistics cost right so you want to minimize the logistics cost you want to optimize the cost you want to optimize the time you want to optimize the route so all three are optimization right route optimization time optimization cost optimization so there are many parameters but you can give a small name like you know latent variable name say which may be a optimization only so that optimization of the hit rate optimization may you know meet all these parameters together you can reduce the dimension and you can make carry forward the discussion of the data and analysis of the data and you can take a better decision so there are many way of you know reducing the data pattern other data like dimension reduction factor analysis also many factors may be relevant to your model right but you cannot take all factor you have to take the most important factors to take forward with the decision making or the analysis further so in that case which factors are more important we can validate that through the experts opinion also so we call them as a you know to some extent factor analysis process also then association rule and recommendation system very crucial in marketing domain actually or you know in IT industry like you know or AI process of association rule like market basket analysis all these things may be you know put under the umbrella of unsupervised learning network analysis text mining which falls under the unsupervised learning of machine learning aspects of predictiveness then when it comes to the supervised learning or predictive modeling which will focus majorly in our courses of business forecasting here you can think about you know classification of models like logistic regression decision tree analysis random forest you know all these are very important look at the regression analysis simple linear regression multiple linear regression will discuss detail of all these things in the session of you know regression analysis module will discuss moving average models exponential smoothing models look at the I have mentioned about exponential smoothing here but effectively under that also there are many models like hold model winter hold model decomposition method all these things will come under exponential smoothing concepts itself will discuss them will discuss also Arima model SCF autocorrelation function partial autocorrelation function auto regressive integrated moving which is most powerful techniques of predictive analytics or machine learning process you study that also to some extent will cover the basic information of the you know different type of machine learning technique like bagging boosting and also you know to some extent support vector machine also or since there are these are couple of models like neural network I will not cover the neural network part in the detail of support vector machine but the introductory aspects of all of them you know unsupervised and supervised learning process I will discuss under the session of machine learning technique as much as possible will try to cover this part then there is another process of machine learning or to some extent you know AI process or you know data science process called the prescriptive analytics. I have discussed in the previous you know session of you know this data decision making session that what are the techniques involved under prescriptive analytics like optimization technique mixed integer programming problem non-linear programming Monte Carlo simulation decision tree analysis Bayesian analysis utility theory they are very important techniques steps of you know consulting or you know statistical decision making we call them as a prescriptive analytics module and then you know game theory multi-creator decision making MCDM technique are very popular in industry in decision making process ranking process and different type of statistical inference all these falls under prescriptive analytics. So, there are three major aspects one is unsupervised learning or machine learning or predictive modeling and then the you know supervised learning of predictive analytics which will focus more on that and then there is a third context that is called the prescriptive analytics which falls under you know the business analytic aspects. So, these are the you know general aspects of you know or the techniques that you should know to become expert in data scientist or the two experts of business analytics domain which you can put all under the model building process. Any software you bring they for throw them whether it is you know advanced excel or the you know python mad layer other advanced software where you are people are people are you know are say people are using this type of techniques through different algorithm and they are addressing practical or cases or practical problems. Then the next step are the model evaluation. Model evaluation is nothing but once you develop the model with the data and you are taking a informed decision through strategy in that case you have to bring the accuracy of the model or the reliability of the model. You can take any model and you can make a forecast right suppose you have a data like this you have made a forecast like this whether this forecast is best or not that you have to you know get to know through your measure of accuracy. So, there are different type of measure of accuracy techniques are there there is a session where we will discuss detail about you know different type of measure of accuracy with numerical examples and the illustration will study all these techniques of measure of accuracy like mean absolute deviation, mean absolute percentage error, mean square error and the root of mean square error like RMSE in financial sector is very popular. So, we will discuss all these things on that particular module measure of accuracy module, but in general what happens now through this model you know evaluation process you need to measure the reliability of the model the accuracy of the model whether this forecast is best or that forecast is best. So, we have to bring the calculate the measure of accuracy and according to you have to make a forecast or comparative analysis that whether your model is best or not like this with the data trial data and the testing data you have to bring the accuracy in the reliability of the model we call it as a measure of accuracy there are many like in regression analysis we use you know R square right in time series analysis we use mean square error even even you know in some logistic regression model or some decision making we use you know RMSE or say you know you can say you know say you know accuracy level between the actual prediction by the total prediction. So, you know accurate prediction by the total prediction this way you can calculate the accuracy level in insurance sector you know or banking sector people use this type of evaluation process whether your prediction model or the categorical model or some different type of logistic regression model that you are using whether your accuracy is above 90 percent or not or how much is the demand threshold requirement that company has provided to you have to maintain that. So, there are different type of you know measure of accuracy other model evaluation process are there you know confidence interval correlation coefficient you can use all this you know like utility of money you can also put as a measure of accuracy and you know different type of optimization threshold value also for them you know expected monetary value also you can use and you can get to know that whether your model that you have developed is really good or bad or how much reliability has compared to your computer or peers. So, these are the process of model evaluation in each and every model you need to evaluate the accuracy of the model through a couple of these techniques that we learn also. Here is another example you can think of the clustering process you can use the clustering of unsupervised learning and look at the data here you may not be able to take any decision right. Once you use the clustering process you may classify the data into different category and you will be able to take a decision whether you know whether the old age people are inferred or not who is buying your product middle age people or the you know to some extent you know younger age all these things you may get to know different type of classification you can do through clustering process came in clustering types and then you can take a informed decision over there which is also part of model evaluation as well as the model building process. So, just couple of points I have mentioned here more detail we will discuss when we will open the sessions then once you evaluate the model develop the model evaluate the model then make sure that you have selected the appropriate model there will be many models which you will study right and you will get to know about the application of them but at the same time you have to understand whether you have understood the context of the model or the context of the data effectively or not and the reliability of the available data there or not because you are taking a summary now you are trying to implement the model right you are the deployment process started now. So, in that case you have to think about the degree of accuracy the desired like the reliability that just now we have discussed about that right the measure of accuracy also forced cost accuracy also time period to be forecast that also very important because now you are going to implement the model to your organization with the data that analysis that you have done another value of forecast to the company how much requirement whether you are meeting the goal of the company or not the objective the research question that you have said that you are meeting it in or not that you have to think also also the stage of product life cycle this is also very crucial for example for startups in the early stage the decision making may be different the forecasting accuracy may be required in a different manner or the you know decision making analytics may be different, but when it will be the existing stage also growth stage the decision making may change the forecast accuracy may change risk measurement may change. So, in that case your analysis also will change your forecast accuracy will be also varying. So, in that case you have to think about at what stage of the product life cycle also time available for making the analysis also it is very crucial if you have a huge amount of data or in a longer period of data you can make a better forecast or you know if you if you have some you know short term prediction or long term prediction that classification you can do and then or based on the availability of data you can also take a decision. So, the time assessment the time availability of data and the requirement for forecast whether the short term prediction long term predictions they are also very crucial. So, therefore if you know these particular you know 7, 8 steps probably you will be able to select the appropriate model that you will learn and you can make a better informed decision through data analytics steps and the processes. So, once all these are done next is the deployment which I have discussed that you know intricate the model the techniques that you have developed to the company and develop a software decision support system or server kind of system where you know you can put the data and you can make a you know database system or you can you know which will reduce your cost increase the revenue bring the operational efficiency you know and improve the customer satisfaction. This is a major step you know by by deploying your model effectively you are solving the case and you are making a good recommendation to the organization that you know follow this prediction model, follow my recommendation and you can automate your decision making you can optimize your business process you can enhance the operational efficiency and increase the market share or the customer experience. So, this is what called the model deployment. So, once this model deployment part are done look at that you deployment of model can be utilized repeatedly on new data remember this part the next step will come here like maintenance or this is called commissioning once this is done you have you cannot conclude the inter decision making process next is that deployment of the model can be utilized repeatedly for no new data making analysis process reproducible and adaptable to changing business requirements with the new technology complex chart, GPT etc. you have to modify your AI process right you have to modify your data analytics techniques. So, once you get more data you might see the data of customer behavior are changing now computer has come back has come to the system you have a many product into the market. So, how you can make better decision based on the availability of data with the new data or customer changes you know by capturing the customer changes the experiences. So, in that case whatever you have developed that may make an absolute unless you modify your data or modify your model and again you redeploy your model again. So, that calls actually you know model maintenance it is very crucial actually model can be affected by data drift and the concept drift remember it if you don't manage the data with and understand the business dynamics over a period of time the changes of customer test and the you know different situation competition etc. if you don't capture that the example that I was giving in the first session of this particular data decision making session think about the example of Nokia think about the examples of you know say or could also Yahoo etc. think about you know the current demand of say Facebook etc. think about you know even Facebook also you know changing with their decision making with the more data and they have entered the metaverse domain think about you know the examples of you know say Geo entering or the Geo into the you know telecom sector and what happens to the both of them they may come back again with their strategy etc. so therefore model maintenance and the deployment is very crucial if even both of them Geo both of them and say idea if they come up with a better analytics process better customer changing policy strategy with a better financing process probably they can also increase their market share so therefore model maintenance is very crucial apart from model deployment so updating your data revising your model and making a better decision or revised decision redeployment of the model is called as a model maintenance or to some extent monitoring and control of the modeling process and the decision making process remember whatever we have discussed the steps first we have discussed about you know data understanding or you know context of the business problem then we have discussed about you know data pre processing model building model deployment and model maintenance if you know this part through three aspects of data given decision making or the business analytics descriptive predictive and prescriptive or to some extent you know aspects of business analytics probably you will be able to you know overcome the business challenges and gain better competitive advantage. This is the summary of so far that two sessions that I have discussed in the previous session and today's session this is a summary actually overcome by understanding data decision making or understanding the basic aspects ingredients of you know essentials of business analytics or predictive analytics probably you will be able to overcome the business challenges and gain the competitive advantage. This is what the advantage of data decision making. If you think about application of business forecasting or the business predictive modeling techniques that you are going to long through this particular courses you know it's it's not limited to this particular you know list it can be applied in detail sector data analytics and the business forecasting and the business prediction modeling are need of the hour actually. So therefore in detail sector also you can think about application of that in manufacturing sector you can use right whether you know focus the production level raw material requirement energy consumption or say you know production planning system everywhere you know you can use this data analytics and so predictive modeling over there also. In detail sector I don't have to give everywhere you know you you require data analytics. In financial sector in banking you know entities are actually implementing the data analytics over there. Even SBI also taking initiative the data analytics for SBI kind of you know like in a branch they have already initiated their branch. Even you go to the insurance sector you go to the NBFC sector everybody is adapting the new technology the data decision making to make their better forecast informed decision making in the financial sector. Healthcare sector the perhaps this is the only sector where you know people are not focusing much on data analytics. Perhaps the most important sector that one should focus or the government or the organization should focus that they should integrate the data analytics in healthcare sector. Perhaps this is the only sector where there is a huge opportunity to explore the integration of data analytics or the business prediction modeling in that particular sector so that they can take a better decision for the consumers for the customers for the patient and for the organization also. Transportation sector also even this they are not only the data analytics people are using you know blockchain also in transport or IoT system also. So therefore transportation system also have a better impact like you know forecast traffic congestion. Imagine you know like you know we will all talk about you know Google map right and and also we are like GPS all these things we see in our mobile when we try drive our car and all these things. But you know most of the Indian companies even also are following are not following the Google product they are actually following some you know map my India product to you know assess the route through their transportation process. You know we are also perhaps following that. So this is one of the Indian company map my India and that is they are using data analytics so effectively that most of the companies are not taking that like advantage of Google's map they are following this particular map my India's product software and they are implementing in their you know tracking system of transportation system. So imagine this is what advantage if you if somebody follow even small entity follow some data analytics and the corresponding you know informed decision-making probably they can also be the winner.  Logistic sector I have already given examples the technical telecommunication sector, media, government everywhere. I as I mentioned these are not only the couple of sector that where you can integrate in which sector you belong in which sector you are going to be data scientist or in which sector you are going to be a consultant not a matter but if you have a expertise in the data analytics and the application domain in this particular couple of sectors probably there will be age in decision-making through this you know courses of business forecasting or predictive modeling. We will try to cover as much as possible all this you know application domain also through when you open different modules of business forecasting or predictive analytics we will also try to give examples from the all these sectors so that you can match or you can map or you can get to know better mapping part between the techniques that you learn and also the application part. So, through the case examples through illustrative examples I will try to cover this particular application aspects also so that that the mapping between the industry requirement and the academic understanding of the technical aspects should the gap should reduce and the you know better insights may be you know passed to you through this course of business forecasting and very essential of predictive analytics. So, with that let us conclude today's session of essential of predictive analytics and data-definition-making steps. Thank you.