Hey, let's jump to cool stuff found John, and you have you have something. I'm eager to hear about yes I have a cool stuff found this is the Chipolo one spot. It's basically of the first Find my network Device that's not from Apple really Yeah, okay. Um, so There's an upside and a downside so one it only supports Bluetooth it does not have the ultra wideband You know, it'll still locate your stuff is just that you you don't get the you know magic circle and and all that stuff When you get close to something but it will you know show you directions on the map as you walk towards it Okay, I see okay, so so this is effectively a third-party air tag without the Same level of granularity as an air tag, right number two it has a hold drilled into it That isn't the problems with the air tag is that you have to get an external holder Here's the other advantage Dave right ready. I'm gonna play a sound. Okay. That's a pretty sound Yeah, but it's also dude. It's like a hundred decibels. It's like oh nice dead loud So is it louder than the apple one? Oh, okay? Yeah apples isn't that loud I mean they cover, you know, they make like a certain pattern, you know Like almost like a radar blip and they are the frequency kind of like this those two But I noticed when we talked we might have talked about this on the show I I noticed that when when I first got my air tags that it it seemed really quiet and Like almost to the point where it was too quiet if I was even in the room with it And then I went four rooms away and I rang it and it was the same volume four rooms away So apples chose in a frequency or a pattern That seems to to carry very well Even though it's not loud


Welcome back to the original gangsters podcast. I'm Jimmy Buccellato aka the doctor in studio with my partner in crime The intrepid mr. Scott birds. Hey now your co-conspirator co-conspirator and Benny's in the house with us and before we get started just want to remind everyone to Please Spread the word Please follow us on social media Twitter Facebook Instagram, please check out our YouTube channel and We're really growing the audience. We're getting more subs more followers And a lot of that has to do with your support and you spreading the word and helping this go Viral so we appreciate that like subscribe share. Yeah, please do it's a it makes a big difference and We got a big big Gambino episode today, but before we get into that related to social media Our sister Publication if you will say a case report Scott wants to mention something an update on gangster. Yeah, so for people that have followed me, you know, since I started my career and I've been Consuming my gangster report web magazine over the last eight nine years. I made a pretty Important decision That was it took me a long time Probably too long to Decide that I had to for the sake of the content for the sake of the audience for the sake of me I really had to change from a ad revenue Business blueprint to a paywall site it just Everybody was losing out And it might be harder for for people that now have to pay for the site to understand that But I hope they would Realize that you know, I got bills to pay. I got a family. I got to spend time with I was giving away really really Exclusive select content for nine years for free and All I'm asking right now is a dollar a week and you're gonna get more Content that you've gotten over the last eight or nine years and you're gonna get more diverse content so Before you were getting roughly I'd say five articles a week now you're definitely gonna get seven to eight articles a week if not more as well as a lot more bells and whistles and you know It was an end of an era and I really enjoyed doing it when it was kind of a Community free for all but now I'm kind of creating my own little You know gangsta report clubhouse for anybody wants to come in and kind of let me lead story time I am I'm honored and privileged and I just hope people will understand that it's really when you break it down If you're someone that consumes it on a regular basis I'm literally asking for a dollar a week for what turns out to be you know an article plus a day Yeah, it seems like it wasn't just wasn't sustainable to keep it because it was open access for a long time Which was very which was awesome and I people like me appreciated that but I agree with you It seems like it's it's not sustainable over the long term And so I think it's a bargain You know hopefully people will take you up on that and just really good content It just for people to you know to contextualize it One one final note here, you know someone said to me like Well, you know it was someone online was complaining about it And I was having a civil conversation with them and I was like what you don't understand is it's either this or I shut the site down Right, it's not like I can't sustain it the way it's been going the last eight or nine years So it's either go to a paywall and invite people to come in for a dollar a week and continue it and and grow it And make it better or just say goodbye and say it was a good eight and a half years And and now I'm turning the lights off. Yeah, that's what it came down to so please check it out and hopefully Yeah, I think it's a bargain. Hopefully people will will continue to support it so speaking of Gangster report you've you've done some reporting recently on the Gambino family in New York in general and in particular Lorenzo Manino and So this is one of my favorite topics. I like to talk about These trans land trans Atlantic connections between Sicilian mafiosi and Italian-American mafiosi. He's one of these guys who's at the nexus of that trans Atlantic So, why don't you if you want to start with some of the? Particulars of your your specific reporting and then we'll launch into a more general conversation Sicilian the Sicilian mafiosi in the United States. Let's give credit work credit is due. I mean a lot of the Initial reporting here was done by Jerry Capace at gangland news he has been reporting on Organized crime corruption within the construction industry It's it's been there forever. It'll probably be there forever and Right now there is a Serbian Gangster organized crime associate by the name of Mike Michael or Michael Michael who is a target of a major major racketeering case he's I believe he's been indicted and It involves, you know him running all of the Gambino's construction rackets and even though Lorenzo Manino who right now is for the last Three four years has been considered the at the very least the acting boss or the street boss of the Gambino crime family since the Murder of Frankie boy Callie in 2018. I believe it was either 18 or 19. I can double-check in a second But they represent the the Sicilian wing of the Gambino crime family that really started to take power in the 1970s with the arrival of the the Cherry Hill Gambino's and Since around 2011 The Sicilian faction of the Gambino's are the shot callers in that organization and they control the administration and the gaudy regime Which lasted from 1985? until the 2000s when You know Peter who was John's brother and one of his successors ended up stepping down and and Italian Dom Suffolk Frankie boy Callie Lorenzo Manino Originally came up under Sammy the Bull Jackie the nose D'Amico These are all names if you follow the John Gotti story that you recognize Mikey scars the Leonardo but now They're the ones that have the power so Jerry has been reporting on that Racketeering case within the construction business and this Mike Michael and how he's connected to the Gambino's and although Lorenzo Manino has not been indicted according to Jerry Capesi sources. He is a prime target of a federal racketeering investigation Into construction racketeering that I'm guessing is either a Companion investigation to the Mike Michael investigation, or it is the Mike Michael investigation and there could be a potential Well, I'm thinking on a term on another indictment a superseding indictment When I should know this on the crime reporter, but sometimes there'll be an indictment that lands and then before trial there'll be Three more indictments that lot land within that indictment, and I'm blanking on the term right now but So it's either that Manino is the target of Separate investigation or he is going to be or could be indicted in the Mike Michael case And they've got wiretaps and this guy was Meaning Mike Michael was employing Manino through one of his construction companies that was kind of like a Shell company. I think it was something. It's called something rebar. I'm blinking on the name right now and we know for a fact that over like a To I'm trying to think of the not I apologize I left my notes at home before I came to the recording It's it's negligence on my part, but I believe that that Manino has taken something like $400,000 from this company in the light over like a two-year period and that there was a $20,000 Bonus that was given to him in the Christmas Christmas 2020 and that there's a wiretap of Mike Michael Talking to Lorenzo Manino about that $20,000 bonus and telling him to be sure to report on your Texas Yeah, so Manino what he's considered an employee of that. He's considered a Consultant I guess but yeah federal government claims. It's a no-show job, right? He's on the payroll getting paid a six-figure salary for not doing anything according to the government Yeah, I mean we were we've had a guest on in the past Jack Garcia who was known as he had infiltrated the Gambino's is Jack Falcone and we're gonna have him on again I think pretty soon, but He he said to us one time that in his opinion not an ounce of concrete gets poured or a nail gets hammered in New York City without the Italian mafia getting getting its cut and and and I suspect that that some of that's hyperbole, but the point is well taken that if you think that The the Italian mafia is completely out of The sanitation business and the construction business and I I've heard that even the garment industry. There's still a Presence an OC but when it's so deeply embedded even if you've cleansed Let's say the majority of the corruption. Yeah, if it's been there It's so rooted and has been there for a hundred years. It's hard to Get that that house that proverbial house spotless There's always going to be little corners of it that are corrupted and in a city like New York with a with a An area where you have five crime families not counting what's going on in New Jersey not counting on what's going on in New England You just The numbers that the percentages go up that that you're gonna have some level of corruption It's just like with the Teamsters like the Teamsters as a general rule aren't are nowhere in the galaxy of the corruption that existed under Jimmy Hoffa, but that doesn't say that that doesn't mean that within the Teamsters orbit that there's not some form of labor racketeering going on Anywhere I can't those are my labor brothers and sisters. I can't comment on that but Yeah, I mean and if you think about the How the how enormous? Commerce is in New York City. This is what this is what I think is interesting about the skill people Maybe don't think about is it seems like when you read the newspapers that Mafia guys are going to prison every day and there's no mafia left. Actually if you look at it from a numbers perspective The mafia still has the advantage The FBI does not have the resources No, they're all the nooks and crannies and all the commerce in New York City You think federal law enforcement has the resources to so yeah They get some big guys and they've taken people down and I get it's not 1950 anymore But if you think that they could they could get into all the nooks and crannies of commerce in New York City and clean Out all that corruption. Come on The federal government's resources. I mean this is a narrative and a and a truth that Has permeated for the last 20 years that the resources have been depleted since 9 11 There's been a distinct shift towards priority in the federal government even more so since Donald Trump took power And this is not a political Editorial whether you pro-Donald Trump or anti-Donald Trump, but the fact is there's been a increase in domestic Terrorism and and issues on the home front in terms of Far right wing and far left wing Craziness, I don't know about that My point is that the resources of the government in terms of going after organized crime We're already depleted and then you add in the climate of our country in the last six years plus and And those resources are spread even thinner Yeah, I mean, I I wonder if that's complicated. I don't know if the feds are I think I think In some ways the feds are under appreciating Domestic would just terrorism just here in Michigan where Jimmy and I are based out of we had a Situation where there was a plot by a militia here a far right wing militia here to kidnap and kill the governor of our state Even that gets and that was because there were a lot of informants Out of like the 22 conspirators like 14 of them were Yeah, it's so then that gets that that becomes complicated too. So I mean, I would say that I would just say that There's no question since 9-11 that a lot of resources have shifted toward counter-terrorism I would take issue a little bit with you and say most of it is toward international Terrorism, but but either way whatever it's not it's not toward organized crime not even in New York City where they used to have each Crime family have their own unit have their own OC unit of the FBI and I believe of the DEA as well Yeah, so you had to get a and maybe even IRS so you might have had three separate federal entities Investigating all five families within each organization So at five different teams in the IRS and investigating the five families five units within the FBI Investigating the five families same with the DEA all trying to make cases that they could intertwine maybe didn't intertwine, but I think there there was a Everybody's on the same team. This is a priority. I mean especially after Hoover died and you know Jagger from the 20s into the early 70s there was not a ton of Federal law enforcement muscle put behind going after the mob when Hoover died that all changed the floodgates opened up It was a trickle in the 70s, and then it was a You know the damn broke in the 80s, but that's an interesting contrast because Under Hoover it was the opposite Hoover was obsessed with domestic political groups Including to the extent of violating their constitutional rights, and he was a really a really bad guy I think if you care about civil liberties and civil rights He was a really bad guy, and he said there is no mafia. Remember and well, I think he was compromised Yeah, that's right.  I think he very well knew there was All this attention for a good 25 years and and that attention had a lot of That scrutiny that microscope that was put on them by the federal government Yielded massive gains for the government. Sure read big benefits Yeah, I mean every almost every crime family was decimated by indictments decimated by informants ripple effects are still being felt today But the fact of the matter is in the last 20 years Whether or not The mafia has shrank and we know it has in numbers But if the people that are chasing the mafia has also shrank then you're you know You're on in you're back on an even playing field. Yeah, and and I think that the guys that are left Are in those industries where there's not as much scrutiny Part of it is because they don't have the resources but also part of it is guys have learned the lessons that You know, if you're going to be whacking people left and right if you're going to be real flashy Then eventually you are going to get someone's intention in law enforcement, but if you stay low-key I mean the FBI When they think that there's a crisis with terrorism whether it's international domestic you got a border crisis all these things You think they want to spend Who knows amount of money infiltrating some construction racket or some bookmaking scheme in New York City Somebody the FBI probably does but they prioritize right and it shifts towards other things So if you can just stay low-key and not make you know not leave bodies in the streets in some ways You're going to be left alone If we're talking about the FBI and those five OC units that have now Consolidated into one or one and a half You know, he's it's bandwidth Yes, you're just not going to be able to accomplish what you accomplished when you have 10 people working for 20 people working five families in one unit As opposed to you know, all those other agencies working on task force or you know multi-agency task force and You know, you had you know each unit would have 25 guys in it now The you know each one of the five units in the FBI going after one of each five families had 25 guys in it now The entire unit has 25 guys in it and they're going after Do the math for me You're going after five times the the amount of people and That makes sense. I'm sorry. I've never been good at and I think Also, if you if to the extent that there are resources toward organized crime the cartels are Increasingly take up more of that More of their you're talking about bandwidth like so in terms of you're going to devote manpower toward something and then and then I would say also like A lot of the attention still seems to go toward street gangs and I have my own theory on that I'm not like I don't know if we want to get racial but and I also just think it's it's it's easier for them It's easier for them to make cases against the games your disciples. Yes, I mean there I mean I'm tracking it. I mean there are cases against games your disciples. Yeah. I mean, this is a group that's Basin, Chicago, but has you know subunits and satellites all around the country. I mean you do a just put a Google alert on your phone You know, there's every couple weeks. There's another bust of a gangster disciple Yeah, and I think those in those in in that case you have a group that's almost Well, for the most part involved in drug trafficking, they are involved in other things, but for the most part drug trafficking They're very violent and they're not insulated Like the Italian mafia is insulated with their political connections or social connections. You have the cartels Which basically it's state capture. I mean they basically have an entire government Mexico so that's a lot more challenging to build a case against The like the cartels or the Italian mafia when they have when they're insulated and have a lot of power as opposed to making cases against Medium-sized drug dealers in their city and and then and it's good headlines that makes Congress happy Oh, we're arresting all these people where I'm not saying just you know that in some cases these street gangs aren't dangerous I understand it there, but we deal with this all the time when you're you know, again, put it put it in the context Mafia the mob La Cosa Nostra The the John Gotti's of the world or the Lorenzo Manino's of the world are romanticized They're not to the to the person watching NBC News Where Lester Holt gets on and tells you about the Gambino bust in New York and they show 485 year old Italian men being paraded in a perp walk That doesn't scare no Joe and Jane American citizen watching NBC News in Lincoln, Nebraska But when you parade ten gangster disciples, I'll hand it out. Yeah, right So what's gonna move the needle for the voters? No, it's a great. No, it's a great point You you're gonna score more points.  Yeah. Um, yeah, go ahead. No, I was gonna say that I think in terms to in terms of organized crime right now The federal government like you said, they're looking at the cartels Um, and I think they're really looking at More recently the bikers because there's been so much instability Um, you know in in the biker landscape and we've dealt with that in the past We'll dealt with we'll deal with that going forward in in in our og podcast But let's do a little deep dive on Lorenzo Manino and kind of tell people who this guy is where he came from I didn't realize um that he was connected to a murder in 1988 and That Manino early in his career I knew he was connected to the cherry hill gambinos. I guess I didn't pay close enough attention to until Until maybe Frankie Callie died or it was murdered um the connections that Callie and Manino who uh, are I guess middle-aged or At the end of the top end of middle-aged or Frankie boy Callie's dead now, but uh in his early 60s is Frankie Or sorry is Lorenzo Manino was 64 right now, but uh until Frankie boy Callie died I didn't realize Frankie boy and and Manino had pretty direct and deep ties into John Gotti and the John Gotti regime Yeah, I mean my research indicates that that um Jackie the nose D. Mico was sort of the um The nexus point between the Gotti's and the and the Sicilian guys because I know Gotti We know from wiretaps that he he was always kind of circumspect about the about the Sicilians. He didn't like that they Always were speaking in in Italian all the time and he made that one funny thing about how like They understand English until it's time to kick up then all of a sudden they don't understand They don't understand English and um, but um and and it's it's interesting That that Gotti used to have to that to show you the Weight that the Sicilian faction carried that when Gotti was the boss When he had to meet with John Gambino Gotti went to him he went to New Jersey Right whereas whereas Gotti was always famous for holding court with John Gambino Gotti would have to go visit him, which is interesting because first of all Gotti's ego But second of all John Gambino was a captain. He was he wasn't even a part of the administration But but but he knew Gotti knew that John Gambino carried a lot of weight because of his connections back to uh Palermo, so Jimmy, why don't we Hand it to you to tell the listeners like let's trace it back to the early 70s or mid 70s when the three Gambino brothers Uh that became to be known as the Cherry Hill Gambino's You know kind of like a a title wave if you will that lands on the shores And uh, you know, there's destruction that is awake from kind of the moment that it hits These guys landed in Cherry Hill, New Jersey at the very end of carlo gambino's reign They were his cousins. Yes, and he kind of places them as a kind of like a family within a family Yeah, they're their father. So you have the three cherry hill gambino's uh, Giovanni Who we call john and rosario and then uh, Giuseppe we call Joe Gambino But those are the three the three big ones, but there's there was actually a lot of cousins other Uh, several other cousin cousins Manny Gambino um, Erasmo Gambino, uh, Antonino Gambino and others, um There was Francesco Gambino the only called cheatsprout. I'm not sure exactly how close he was related to the these other Gambino's but Um, anyhow, if you look at the three main brothers Their father and carlo gambino were cousins going back to Palermo. So when they come to the united states carlo pulls some strings for them Gets them set up with uh different businesses and um so they uh, were very close with Carlos brother Carlos brother paulo gambino who was a captain was sort of like the unofficial Head of these new zips that were coming in to and they placed them as a buchetta was one of those guys that came in he wasn't with the Gambino's back in cishley, but he knew them and he was uh, Amici with them. Here's what's interesting geographically is that it They placed them In cherry hill, new jersey, which is a suburb of philadelphia. Right. I mean you're 10 minutes from philadelphia in cherry hill So you were putting them smack dab in the middle of bruno crime family territory, right? Which speaks to the relationship between angelo bruno and carlo gambino in the 1970s and it also foreshadowed some of the animosities that led to angelo bruno being murdered in 1980 and then castellano uh, who was carlo's brother-in-law and um Successor, you know his famous murder in 85 which allowed god to take power. Yeah, so, um We've talked about that with some of our philly episodes, but because carlo was close with angelo The gambinos are allowed to set up shop in their territory, which as you pointed out under other circumstances A don it you know in their territory may have viewed that as um encroachment But the bruno was gave the green light to that and then to add insult to injury As you mentioned in another episode Especially toward the end of his life angelo bruno was aloof with the rank and file But he would hold court with the cherry hill gambinos all the time and take dinner with them And take envelopes from them have christmas like how to spend the holidays together We need call his own documenting but he calls own soldiers on the carpet for dealing drugs Yes, right because he thought that was bringing them heat, which he was worried was going to turn into them flipping on him but He would take money from the cherry hill gambinos that that were drug money You know one of his closest advisors of that time was long jaromontorano who was the you know the um The meth kingpin of america. Yeah, right in in his uh, mob heyday And he and he was um, so there's a lot of hypocrisy, but also bruno was um Allowing the cherry hill gambinos to open up restaurants and bars throughout philadelphia atlantic city and um You know In that world some of the italian-american guys view this as a zero-sum game Like if if the cherry hill gambinos are opening up construction companies and bars and restaurants that means that i'm I'm not right. I'm i'm losing out and these guys are pushing age and making a lot of money So there was a lot of resentment toward um toward bruno, but it's it's really fascinating because it gets wound up in all these other aspects of of mafia politics because um The gambinos Are part of it gets confusing They're part of a mafia super clan and what I mean by that is genealogically Not necessarily an organization Because they're spread out among different organizations in sicily and then and then in new york You could even if you want to say los angeles with if there's if that's Even a thing today with tom again the rumor the rumor is that one of the cherry hill gambino's sons Was sent out to la. Well, that's not a rumor. He wasn't out there The rumor is that he's the boss of the la mafia. Yeah, whatever whatever's left. So but but the clan itself is gambino inserillo Spatola and demaggio and part of that clan includes Carlo gambino Paul castellano, they're all if you look at a family tree of this It's very wide and it's so interconnected and these families all Intermarried with each other in some cases. They married each other's cousins like in some cases Gambino married another game, you know, carlo gambino married. I believe probably being I believe carlo gambino's wife was his first. It's first. Right now. It's fourth. Yeah third cousin. Correct me if i'm wrong mob archaeologists out there that uh, we love shout out to the mob archaeologist podcast. Oh, yeah, yeah, right on Yeah, i'm glad you uh, you mentioned that. Um, we'll figure out a point where we can like collaborate with them on their show and our show but um, so They're very powerful and the the different families are uh, they're members of other crime organizations like the gambino crime family in york different crime families in the palermo area. So they have a lot of clout and they're Very much involved in drug trafficking by the 1970s and and early 80s and There's a shift in mafia politics in sicily happening around the same time where the power is shifting away from palermo and those those clans that i'm talking about toward corleone especially toto reena but all his guys provinzano bagaralla those guys and A war breaks out. It's it's called the second great mafia war and which is it's actually Not a really the best way to describe it because it's really a massacre The corleone's they didn't lose any they didn't lose anybody all the casualties around the other side It was in the late 70s early 80s. Yeah, you had hundreds of bodies. Oh, yeah, it was very it was Nothing's on par with the cartels, but if you were talking about the Italian mafia, that would be as close as Closest thing you could you could where they were killing prosecutors judges as well as other mafia members and it was a real massacre and Corleone They were at war with almost all the old school families which included the super clan of demaggio in zarillo gambino spetola and They're getting they're they're killing them and This gets complicated because remember a lot of those relatives are in new jersey and in new york and Either full membership in the gambino crime family in new york or at least associated with the gambino so Paul castellano has to intervene at one point and and put sends the word sends john gambino john gambino Goes as a what would you say like an ambassador or something to sicily to meet with uh totorinas people and say We got to figure out something here because castellano like he's related to a lot of these people and totorino is smart enough to recognize that It's fine if you want to kill everybody in palermo But you you you have you need new york you you need to maintain positive relations with new york so they they worked out a deal where um totorina allowed some of those members Of that super clan to migrate to the united states as long as they would never set foot in uh sicily again But it's complicated because there were some people That totorina said even to paul castellano. He said no exceptions There's a there's a couple of them that that For this deal to to be go through I want them dead and so It just shows you how treacherous this world is The cherry hill gambinos basically had to kill a couple of their own relatives in in jersey, right? Um, which um This was on bruno's territory and I I think in one case they even used bruno shooters, didn't they? Yeah, well there was a situation with the um The two brothers god i'm my my my selena brother the selena brothers. Yeah, uh, who were a terry hill gambino's crew members who Got too big for their britches and according to informants uh Uncle jola gambi and yogi merlino right right were involved in those murders. They were charged the eventually those charges were dropped but uh at the time it looked like nicky scarfo was giving The cherry hill gambino nicky scarfo was angelo bruno's one of his successors was giving the cherry hill gambino's shooters right right and in order for these guys to get their bones and and uncle jola gambi went on to become a boss of the philadelphia mafia He stabilized that family in the late 90s and 2000s. He's now the kind of de facto uh concillary and um yogi merlino's The boss of the philadelphia mafia joy merlino's uncle who eventually turned government informant and the and the selena brothers that that's uh gets pretty tangled because that because Which merlino was the one that became the chuckie was that yogi? yogi became the informant yogi chuckie was the underboss yogi claimed that the selena brothers were That that was an internal thing between the cherry hill gambino's and them over over money So was that related to the politics going on in cisley? I don't know, but we know that around that same time pietro inzzarillo is found um in a trunk in 1982 and then antonino uh inzzarillo goes missing around the same time and those were Agreements that the selena brothers was 83. Yeah, it might have been 82 or 83. I can't remember um, but Those were agreements that basically the cherry hill gambino's had to concede Um, so it's really it's really tragic because these are their own their own relatives. So let's let's trace manino um into this group now So lorenzo manino again, I don't know why I didn't realize that Frankie boy cali and lorenzo manino who were kind of a uh, a duo a tandem if you will um They rose through the ranks together. Yeah in the 90s and 2000s to the point where they were in the administration in the 2010s uh Manino, I'm sorry. Let me just interrupt you for a second. I apologize. What's interesting about because Frankie cali I think it's sort of like for people to follow this is a Everyone knows who that is Frankie boy cali for people that might not know Became the boss or the at least the acting boss or street boss of the gambino's Um, was you know, he was the golden boy in the new york mafia. Yeah younger guy Yeah, and then he got murdered about four or four or five years ago in a very strange non mafia related uh, some mentally ill Right winger that was dating his niece or had maybe had been infatuated with his niece Who lived with him and his wife? He thought shelly was part of some like human trafficking Some he's making a citizen's arrest and he showed up at the guy's house and lord him out of his house Um under the pretense that there had been a car accident and then shot him in the back Yeah, that was that was pretty and I can't think of any parallel example in organized crime history at the time and jimmy and I This was right before we I think we as we were starting the og pod um But I remember talking to jimmy right when this was happening and there was a lot of speculation that this was the Goddys coming the gaudy Faction of the family coming after the Sicilians right and it was going to be the start of a civil war It it happened around the same time that gene goddy had came out of prison Who was john goddy's uh most trusted brother? Yeah, and everyone was speculating there was and that wasn't what the case was No, what turned out to not be the case but because because cali was more of um Make I think was more of the you know in the newspapers What I think is interesting about manino is And and and we think of his fortunes being tied to cali But lorenzo manino was on people's radars way before franky because lorenzo manino We you know, I have government documents here Spread out in front of me that talked about lorenzo manino being joe gambino's quote right-hand man As early as the 1980s the joe gaming or john joe okay joe Be because at that point john's higher right lorenzo would have been too young to be that close to to john at that point so um, I think it's just interesting that um We think of manino as sort of like the successor to cali But actually manino's ties go back just as just as deep and just as far if that makes sense And they allegedly all report uh, italian dom syphilu. Yes Who's supposedly the kind of the bigger head? Yeah, that's the younger Younger sustenance when I say younger lorenzo manino's 80. Sorry. He's 64. He's not that young Yeah, it'd be interesting to ask some of our gambino people that we know for more details, but Again that speculation that oh, this must be the gaudy faction going after franky cali that that speculation at first But but when you realize when you look through the documentation and he talked to other people Actually, they they have pretty good terms. They have pretty good. They have actually have pretty good relations with each other Yeah, the gaudy people and the Sicilian so in a way And I admit I didn't I didn't see that at the time But with the hindsight we could have said like well that actually doesn't make sense Because they're they're actually there isn't really this tension between between the two groups at least not that I can tell so manino Made his bones and got his button in 1988 um was sponsored by I think it was like a Coalition of the cherry hill gambino's and sammy the bull Who oversaw The murder that lorenzo manino participated in To earn him entry into the gambino crime family and I just want to you know discuss that for maybe Five minutes ten minutes as we as we start to kind of wind down here because It's it's pretty compelling. Uh, it was a murder that was Saw it for a green light by john gambino the the kind of the first of money first among equals of those brothers As the leader of the cherry hill gambino's and you had a situation in early 1988 where you had It might have been a distant cousin of theirs. I'm not sure the guy's name was Giuseppe Gambino and he lived um in The same apartment complex in Astoria, Queens as a guy named Frank Francesco Auladeri who was a Sicilian immigrant Who worked at the ranzani pasta factory? um and Was according to informants. This was never charged. I'm not trying to uh Smudge a man's reputation when he when he's been dead for 35 years, but mr. Auladeri was alleged to have been involved in drug dealing with the cherry hill gambino's specifically this cousin of the gambino's Maybe i'm using the term loosely but Giuseppe Gambino who isn't the same? Not joe gambino. We're talking about as being the the mentor of of lorenzo manino. So one of the cherry hill gambino's lives in this apartment complex in queens with the the Sicilian immigrant, uh, francesco um, Auladeri who lives there with his wife and five kids. He speaks kind of broken english um and is supplementing his income at the pasta factory allegedly with dabbling in drug deals one of these drug deals goes wrong um and a feud develops between the neighbors and in February of 1988 francesco Auladeri stomps Giuseppe Gambino to death beats and stomps him to death in the apartment complex Um this Gets a murder contract placed on francesco Auladeri's head John gambino Is adamant that he has made an example of He travels to both uh ozone park To the burglar and fishing hunt club as well as the ravenite to discuss this with John Gotti and sammy gravano And it's decided in april that they are going to carry out the hit and Gotti himself puts together the hit team um Which i found which i found very yeah boss compelling again. Yeah, you're supposed to delegate those things so um John gambino of the of the cherry hills wants lorenzo menino On the hit so he can propose him for his button Joe gambino who is lorenzo menino's mentor is also on the hit Sammy the bull is going to be there and then Gotti recommends a uh, a new jersey gambino Soldier by the name of bobby cabert. I'm not sure how you pronounce the last name jimmy. Can you pronounce it? I don't want to butcher it Oh, yeah, um Bisasha so robert bisasha Was known on the thing i was known on the streets as bobby cabert And he got the name cabert because he was a world-class softball player And he would throw a lot of strikeouts So instead of calling him robert. They called him cabert. It became a nickname um, and he was someone that was known as a shooter as a guy that was known as a uh Someone who paints houses Okay, and uh, don't bring that up. I'm joking. But known as a guy that was was capable and uh, was someone that had had murdered before And was already a made member And this was for bobby cabert to become a coppo. This was going to get him promoted and then a guy named or another Potential soldier who became a soldier irasio stantini Went by the nickname azi and azi stantini was brought into it by Gravano Because gravano wanted stantino to get a stantini to get his button Yeah, so each guy had john gambino gravano godi have their own guys that they're right And but they none of them i guess i shouldn't say i don't know if they knew or they didn't know But bobby cabert really had nothing to do with this It was simply inserted at godi's request because he trusted cabert to be the trigger man um, and this conspiracy Went on for a good month uh of planning and there were actually Tactical meetings that were taking place at the raven night. Yeah in in little italy uh the night before There were two attempts made on alivary's life one attempt was unsuccessful on april 26th and on that night, uh that whole hit team met at the raven night with gravano and godi and then they they had discovered that alivary Lived well, they knew he lived at this apartment complex and they they were able to be tipped off that he had a parking permit that Switched sides of the street In the morning so where he parked at night he parked on Uh one side of the street from seven o'clock at night to seven o'clock in the morning when it became O'clock in the morning he had to move his car to the other side of the street So they knew that every morning at about seven o'clock he would leave to go move his car It was an al a white alpha romeo He was staying true to his roots. Yeah For a guy who works at the ranzoni plant It's a nice car for So they show up on on the morning of april 26th and they missed him They missed him by like 10 minutes. He had already moved the car They show back up A week later, I believe it was may first or second And uh, they're they're in two different cars Gravano is on is on site with manino manino provides the murder weapon To bobby cabert and bobby cabert Successfully guns down alivary as he's going to move his car that morning The case or that murder gets rolled in To a drug racketeering case that's brought in 1993 There's a trial That ends in a hung jury And instead of going back to trial Manino pleads it out admits to his role in the alivary murder as a predicate act To the racketeering conviction and ends up doing about 12 years in prison walks out in 94 Or sorry walks out no four Went in in in like 91 or 92 And it shows you this case study shows you the importance of Being a made guy because the cherry hill gambi and by the way, we I don't know if we clarify this I can't remember but cherry hill is a city in south jersey That's why we keep on saying well We also said that it's more of a or it's not more of it is a suburb of philadelphia Yeah, it's not part of the new york jersey. It's about five miles from philadelphia. That's right right right there But that's why we say cherry hill gambinos. Yeah, and at one point actually a lot of those guys Actually didn't move back to new york, but we it's we still call them the cherry hill gambinos because it's just I don't I think has a cool has a cool ring to it. But anyhow, um The cherry hill gambinos and I think we've talked about this a little bit in some other episodes Maybe philly episodes the cherry hill gambinos had dust-ups with guys in the bruno scarfo family But no one gets whacked Because you're both made they're both made guys and so you have there were some sit downs One of them happened with castellano when he was still boss one of them when gaudi was boss but i'm saying oliveri He's got no He's coming the guys that he would run to were the guys that he had a beef with Right, right. So he's just they're just gonna whack him So it shows you the importance of in that world having the right connections or or even, you know Having membership because if you're not sponsored by anyone or protected by anyone And you get on the wrong side of a made guy Your days are probably numbered and at least back then so menino Provided bobby caber with the gun That killed francesco oliveri, but he also provided the cars that were used In the hit and one of the ways they were able to tie menino to the hit was that they had Phone records from his car phone and it's funny to think of what a car phone looked like in 1988 Yeah, it was you know the size of the the rock of debrauter Um That he they had phone calls from him to the auto dealership where he was renting the car Renting the cars from Um, so he was part of the logistics. Yes, and he was there. Yeah, he was on scene and they had walkie talkies They were right. He provided the walkie talkies as well. Uh, so how did this case get solved? well, sammy the bull gravano flipped in in 1991 and uh Spilled the beans on what happened in the in the francesco oliveri murder as well as another you know 12 13 14 15 hits But that's the that was the hit that did lorenzo menino in he got his button though. I believe in the fall of 88 um He was in that same I don't know if it was the exact same Induction class, but it was in the same couple months that john goddy jr. Got made because I know that john goddy jr Um, and mikey scars were both made in Christmas eve 1988 ceremony What do you think it what do you think of this says about like one thing that's curious I find curious is so lorenzo is able to It makes a he please out, right? John and joe do the same thing For the cocaine and heroin Conspiracy they actually went on the lamb for a while. They got caught in florida um Old school rules it doesn't apply now ever everyone please out now, but the old school rules were You're never supposed to take a plea you never acknowledge I mean the cheer John and joe basically admitted that they were members of the mafia and fall the drug trafficking to get a lesser sense They didn't snitch on anyone But i'm saying they they admitted in court that they were part of this criminal conspiracy You're not supposed to in the old school ways you were not supposed to do that especially in the goddy regime or at least the early Goddy era when john goddy himself was on the street or in the first couple years when he was behind bars And he still had some some uh some some shot calling authority, but uh, he was adamant Yes, that nobody take pleas right so like you're pointing out This happened in 1994 now goddy had only been in prison for three years You would think that goddy at that point still had some sway in decision making his son was running the family Yeah, uh, but it didn't seem to apply To the two gambino brothers or lorenzo manino, right? So what do you think that's is that was there there could be two things and let's see what you think about this either a Because goddy's in prison. He's his his reach is already starting to yes, you know It's not as it doesn't reach as far and then also because the Sometimes the the zip factions seem to have their own right. I think I think it's rules and norms that I think it's both and I think uh Like I said earlier when we introducing the cherry hill gambinos as an entity They were a part of the gambino organization, but they were kind of a island in its own right. Yeah, where they kind of have Governed themselves to a degree and and john gambino even rose to the point in the 2000s and 2010s before he died. I think he died about four four three four five years ago He was on the on the ruling board So he was one of the the guys that was actually running the whole gambino organization not just the cherry hill group yeah, and um And you want to talk about another? Cross-connection here talking about the selena brothers and uncle joe legambi being the alleged one of the the trigger man on one of the selena brothers hits Joe legambi was caught famously on a wire in 2010 and 11 Having dinner having a lunch meeting with john gambino. Yeah to discuss family business between philadelphia and the gambinos and they met at a place called lagrilia in new jersey And it was a a four-hour meeting that they had the The whole thing taped well It's interesting that the cherry hill gambinos to show you how they're always able to weather these storms because They're related to paul castellano And when god he has castellano killed God he has to make sure with the cherry hill gambino is like Are we good? Because that's yeah, I know that's your relative and and they they worked it out. They knew what was good for business Yeah, and then you have a similar thing with with bruno to scarfo like it doesn't It doesn't like there's and then to later on tomorrow. They're always keeping these good relationships When possible think about though from the from the gambino administration in the post-castellano era You were okay with drug dealing. Oh john god. He was a drug dealer. Yeah, so You're probably more prone to Yeah, you know bestow leniency on this drug dealing crew without you know that even though castellano was looking the other way Yeah, it still had to be something that was of course kind of known about but not spoken about Yeah, because publicly he still had this no drug I mean and that's really what was the crux of the castellano goddy beef I mean it was kind of the straw that broke the camel's back and there was a lot of Uh, there was a lot of other issues at play that were leading up to that but what things came to a head was because Goddy knew that castellano was going to get a hold of those wire tap tapes And it was going to show that godly goddy was fully aware of a giant heroin Uh, yeah organization within his crew quack quack with his best friend regeria angelo regeria with his brother Gene goddy And they were moving huge amounts of H and castellano was Very very vocal about if I find out that you knew what was going on. I'm going to kill you and I'm gonna kill your brother Yeah, and it there's a lot of hypocrisy there just like bruno because he was taking drug He knew the same guys that bruno was taking drug money from so was castellano And I think there was always this kind of um thing of castellano and bruno trusting The Sicilian guys to traffic heroin and not get in trouble and get pinched, but they didn't trust Guys like well quack quack I would trust john gambino before I would track angie regero Seven times in a week twice on sundays. It sort of makes sense, right? And indian ginger for people that are interested in a little, you know tidbits and and little um interesting uh anecdotes angie regario Who was john goddy's best friend? They called him quack quack because he couldn't keep his mouth shut he Thought he was being slick and having all these conversations about drug dealing on his 14-year-old daughters like uh, my little pony phone It was like a pink phone and like the uh Like literally like it was like shaped like a like a horse or a unicorn And it was in she had her own line and think about this in like 1982 83 A 14 having their own line and they're better than those pretty extravagant And and angie regero thought that you know, they might have a bug on my home phone But they're not going to have a bug on my 14-year-old daughter's phone Well, yeah, unless there's someone that you're dealing with who's a snitch that knows that you're using your 14-year-old daughter's phone And they're going to tip the government off and they're going to put a bug on that phone Yeah, and he was very He would talk very openly right and that those were the wiretaps that cast lano was desperately trying to get his Hands on that the goddy crew was desperately trying to prevent him from getting his hands on because not only Were they talking about drug dealing?  Oh, yes, and the faculty was cheating on carlo gambino's sister with the the hispanic Maid and now he was going to florida to get penile enlargement Surgery and they were dishing they were dishing and those in those tapes And so yeah, and but it's really interesting. I mean you could just go on and on we we're running out of time here But the cherry hill gambino's we didn't even get to they're also at the center of that Vatican bank scandal the piece in the piece of connection right so they're they're really interesting Not only touching upon philly new york, but but international stuff. So so it's interesting that even today guys like lorenzo menino and Giovanni Inza rillo who was a maid guy with the gambino's but he's now in back in palermo and I and just not long ago Tomaso Gambino was busted in Sicily and that's that's joe's son. I believe Yeah, it's tommy's. It's tommy's brother. No, no, Tommy. Tommy's first is rizario Because tommy's father is rizario who's also was arrested not that long ago after being deported from the united in Sicily And so even now even though like john's dad and frankie kelly's dad. They're still they're still making headlines if you believe Scuttle, but tommy gambino leads what's left of the la mafia. He's a guy that Is you know out and about he's not hard to find in la he rubs elbows with some celebrities and and hollywood elites and You know, who knows there and I reported in the last year or two That he he was making people at the request of Buffalo Yeah, there were some canadian guys Yeah, and some canadian guys that were getting made so they could do business on behalf of the todaros And that they had reached out to tommy gambino in la We're going to send this guy over to you to make them and then one of these guys comes back after getting made He takes his family on a disney disneyland trip. This is according to the informant We don't know this for a fact, but in One or two informants at least one informant tells the government that this ally of our owny guy Goes to la with his family to take his kids to disneyland he Takes off in the middle of the family trip to go meet up with tommy gambino who makes him um and then you know a week later when he gets back to Buffalo or I don't I don't remember if it was in buffalo or if it was in hamilton Which is the I think he was hamilton hamilton ontario and he gets back to hamilton, which is right next to buffalo Like you could live in hamilton a working buffalo or you could work in buffalo and live in hamilton Uh, and yeah, he a week or two when he gets a week or two after he gets home from that trip to california.  Frankie boy cal Frankie boy cali's brother-in-law was tall peter inserillo Who's a captain in the gambino's now? Yeah, I know we're throwing a lot of names at you people and if we if jimmy, I have a hard time keeping them straight We can imagine uh that you guys are swimming But uh, we thought we think we got we got to the the meat and potatoes of of lorenzo menino and where the the Gambino crime family stands right now that the sicilian uh group within that organization You know, they're the ones that are the the straws that serve the drink right now And you know last thing i'll say about lorenzo menino is you know, I did some due diligence over the last couple weeks and and reached out to some FBI sources that I that I have and and some some wise guys that are have dealt with him And lorenzo menino is as jerry capace. He said in his in his original column that that approached the subject He's the real deal and he's a guy that has uh universal respect um, he is someone that is Very business savvy very sharp Uh is respected on the street. He's respected in the board room He's a guy that gets a lot sides of the atlantic. Yeah, so, you know, check let me say he checks a lot of boxes um, doesn't have any At least what we know doesn't really have any enemies.  Is it mickey boy or mickey boy? Uh michael paradiso. Yeah So that's where we stand. Um This was fun. Yeah, hopefully we'll do some more east coast, uh lcn um Episode soon. We know they're popular. Uh, we like to have diversity and look at other crime families, but uh There's still a lot of action on the east coast. So we'll we'll we'll continue to cover. Yeah I'm going to make a more concentrated effort on on bringing more new york lcn Into into the og pod as well as gangsta report because you know, you can't really cover the mafia in america without At least having a a focus of some degree on on new york city the big app Yeah, that's that's the nexus of all this so anyhow, uh, thank you for listening Please again, spread the word follow us like us and uh on social media and we'll see you next week. I'm jimmy butchilada scott bernstein. We're out


Namaste, welcome to the next module of practical machine learning course. In this module we will study the techniques around model evaluation. So far we looked at other steps in machine learning like data gathering, transformation, defining models, defining loss functions and training the model. The final step in the machine learning pipeline is really the model evaluation. In model evaluation we are concerned with the question of how well the model will work on the unseen data and we are also interested in diagnosing the problems like under fitting and over fitting with the model and taking the corrective actions.  Let us begin. So, as I said we expect model to work well on the unseen data. Now, how do we really test the performance of the model on the unseen data? More than unseen data we really want model to work well on the future data. We train the model on the past data, but we want to make it work on the future data and we do not have the future data in hand. So, how do we really solve that particular problem? So, one way of solving that problem is taking the entire training data and dividing it or partitioning it into two parts. One is a training and second is a test. We use a large chunk of the data for training and hold out a small percentage of data for test. Usually we follow 80 percent data for training and 20 percent data for testing. And the model will be trained based on training data, test data will not be exposed to the model. Model does not get to see the test data. If by any chance your model gets to see the test data, then the performance that you report on test data will not stand the scrutiny of the time. In a sense that you might get over estimation of the model performance if your test data is accidentally leaked to the model in the training time. How do we really measure the performance of the model? So, there are standard measures of performance. So, in case of regression we have squared error, mean squared error or mean absolute error. So, here we take the square of the difference or square of the error between the actual value and the predicted value. Here we take the absolute difference between the square and calculate mean of that. So, these are two measures that we use in case of regression. In case of classification, we first compute the confusion matrix or we first come up with a confusion matrix or we first calculate or fill up the entries of confusion matrix and we calculate measures like precision, recall, F1 score to measure the accuracy or to measure the performance of the classification. As you also use accuracy as a measure, accuracy as a measure is not stable. It does not work well when your data set is imbalanced, when you have way too many examples from one class and too few examples from the other class, accuracy is not a good measure to use or it is not a good metric to use. Apart from that we use ROC curve and PR curves to understand how our classification is working across different thresholds. So, you will go through each of these terms in detail or later in this module. So, it is enough right now to understand that we will be using one of these measures and reporting performance on the test data. How do we believe that the model that worked well on the test data is also going to work well on the future data? So, why do we really believe in this? So, here comes a very important caveat in machine learning. We assume that the training data and test data are going to come from the same distribution. If training data and test data is not coming from the same distribution, we do not have much hope. So, let us understand what do we mean by training and test data coming from the same distribution. Let us take an example of a kid preparing for an exam. We tell the kid to prepare to come prepared for maths exam and the next day we give him questions from the maths, maths textbook or maths syllabus. So, here since kid has already prepared for maths, he will be able to answer questions about maths. So, this is a nice example of training and test data coming from the same distribution. Now, imagine a case where we ask a kid to prepare for maths, but we ask questions in science. So, the kid would not be able to answer those questions because he never trained on science. This is an example where training and test data are different. So, this is an important caveat to note that machine learning makes an assumption that training and test data comes from the same distribution. So, now that we have learnt how to train the model and evaluate it, let us try to understand three possible scenarios that can happen to any model after training. So, your model will either under fit or it will be the just right fit, it will over fit. Let us try to understand the three concept through a diagram. Let us say you have a model that has a single feature and it is predicting the value y and let us say these are data points. So, if I believe that my model, so let us say my model is a straight line that means it predicts some constant value. So, let us say my model is y is equal to 2. So, no matter what is the input, it always predicts the value 2. So, this is an example of under fitting where the model is not taking into a counter training data at all and it is going by a very strong bias that no matter what is the input, I am going to spit out the output which is a constant which is a fixed number which is 2 in this case. So, the second thing that could happen to your model is that it will be doing just the right fit. So, let us use this particular color and this is an example of just right fit. So, it appears that the points are, so the points are around the line. So, a linear model might be just the right fit for this particular model. So, this is the category of right fit. So, the first one that we looked was under fitting is an example of over fitting. In over fitting, you end up achieving a zero error on the training data, but your model may not generalize well on the future data and one of the important thing that we care about in machine learning is to have a model that generalizes well on the future data or that makes better predictions on the future data. So, one of the goal in machine learning is to build models that make good predictions on the future data rather than on the past data. So, that is why over fitting is bad for us. So, if you slightly perturb or if you select any other point on the training data, you know the over fitting model would not be able to predict it. In over fitting, the model is literally memorizing all the data points, all the input-output pairs. So, we studied, so there under fitting and over fitting is our problem and we understood what is under fitting and over fitting. Now, what is, now the next question is how do we really diagnose under fitting and over fitting? So, in case of under fitting, we are using a model with a single parameter which is bias, whereas in over fitting, we are using a polynomial of 7 degree to get a perfect fit on the training data. So, these are problems of either there are too few parameters in case of under fitting or there are too many parameters in case of over fitting. So, our job is to come up with right set of parameters for getting just the right fit. And, let us define the complexity of the model or let us define a major of complexity of the model and one of the major is the model complexity is measured by number of parameters that are used in the model. So, in case of under fitted model here, the model complexity is just one in case of number of parameters. Whereas, in case of this degree 7 polynomial, there will be far more parameters than the under fitted model. Whereas, just right model has two parameters, one parameter with respect to the bias and second parameter with respect the second parameter which is a coefficient for feature x 1. So, what we can do is we can actually draw, so on x axis we have what is called as model complexity which is defined by number of parameters. So, let us say it starts from 1 all the way up to whatever a very large number here and what happens is that this is a major of loss which is j or any other metric from evaluation you can use here. When you have two few parameters, the model generally has very high loss and as we go on adding more parameters, the model will become better at training error. So, model will have lesser and lesser training error, this is the training loss. Now, we have to understand whether model is under fitting or over fitting. So, what we do is we have already divided our training data into train and test part. So, we take this train part of that and we divide it further into two parts. One is called the train and the second is called dev, dev set or validation set. So, we measure the training loss on the train set and we also measure the loss on validation. So, note here that validation data is not shown in the training algorithm at the training time. So, whatever loss we are measuring on the dev set is similar to the loss that we measure on the test set. So, we will get dev loss. So, what will happen is the dev loss or the validation loss will reduce initially as we increase a number of parameters in the model or as we increase the model complexity. After a point, it will shoot up. So, no matter how many more parameters you increase, the training error will go down and keep going down, but the validation error keeps going up. So, if we look at this particular graph, it seems to us that this is probably the sweet spot where the validation error is low enough and training error is also low. Beyond this point, validation error has shot up. So, this point corresponds to just right fit. On the right hand side, we have overfitting. What is happening here in case of overfitting? The validation error initially improved, but after a point it went up. So, if you see this kind of pattern in the training error in case of in your learning curves or in the model complexity versus the loss curve, we can be sure that there is some kind of an overfitting happening. Whereas, this particular part to the left of just right is called underfitting zone. It is an underfitting zone. So, we do not just we simply do not have enough capacity or we do not have enough parameters in the model to achieve lower training and validation error in this particular part. So, if your training error and validation error is high, we can assume that there is some kind of an underfitting happening. Whereas, if your validation error went down before going up, then we can say that we have an overfitting happening. In case of just right fit, we have training and validation error both low and then we get a model which is probably just right fit for the data. So, this is more like an exploratory exercise where in order to so, you will have to you will have to conduct multiple experiment starting with simpler model and adding more and more parameters to it and checking out the training loss and the validation loss. The training loss is computed on the training set. Dev or validation loss is constructed on dev or validation set and we observe the patterns or we observe the numbers or we observe the loss to figure out whether we have an overfitting situation or an underfitting situation. And there are you know based on once you understand what is really the problem with the model, we can take corrective actions based on that. So, let us try to understand how we can fix underfitting. So, once you recognize that underfitting is your problem that means, your model is not getting not getting lower loss on validation and training set, both the losses are high. We can infer that probably model does not have enough capacity or model does not have enough parameters to learn the training data or to learn the model on the training data. So, what is the solution here? The solution here is to increase the complexity of the model because your model simply does not have a capacity to learn patterns from the training data. So, here one of the solution that works well here is to add more parameters to the model. How do we add more parameters to the model? Either you get more features or we can do, we can construct features by crossing the existing features or by constructing several polynomial features of different degrees. So, for example, concretely if you have two features x 1 and x 2 in the original model, we can construct the features of polynomials of degree 2 by raising the power of each of the features and by taking the cross or by taking the feature cross or by taking the feature cross which captures interaction between two features and when we do this, we are automatically increasing the capacity of the model. So, feature crossing is a standard way of increasing the complexity of the model. Now, how do we fix the overfitting? So, let us why does overfitting happens because we simply have too many parameters. So, one way of fixing overfitting is straight away getting more data. If you get more data, we will have enough data to train for the complex model or model having large number of parameters. Second is we can reduce the model complexity. So, one way of doing this is through regularization. Here the idea is that we will penalize the model for being excessively complex. So, you remember you must be remembering the loss, this is a loss function, we have a loss function and in loss function we are trying to minimize the loss function. So, we add a penalty which is lambda times is lambda times the model complexity. So, our new loss function becomes the loss plus the penalty for the complexity. Lambda is the factor that controls the weight or controls how important, how much importance to give to the model complexity. It is called the regularization rate is lambda and there are various ways of, there are various ways of calculating model complexity. So, one way to calculate model complexity is called L2 regularization or ridge regularization. In this case what we do is we calculate the second norm of the parameter values. So, essentially what happens is we calculate the second norm and we add the second norm as a penalty. The effect of this is we cannot have a model that minimizes the joint objective by assigning a very large weight on one of the feature. So, that would not be possible with L2 regularization. So, one way of measuring model complexity is with L2 regularization which adds the second norm of the parameter vector. The other measure is or the other way to do this is through L1 regularization where instead of using the second norm we use the first norm or the absolute value of the parameter of the parameters. So, this actually simplifies to 1 to m w i whole square and this simplifies to 1 to m absolute value of the parameters. So, by adding these penalty terms we are able to control the model complexity. So, if you are, if you have the problem overfitting it is good it will be a good idea to increase the value of the regularization rate or lambda. So, if you increase the value of regularization rate here what will happen is that we will be giving more importance to the model complexity. So, we will be we will be applying more penalty. So, if you have if you are suffering from overfitting increase the regularization rate. So, sometimes people also combine L1 and L2 regularization together which is called as elastic net regularization. So, those options are also available to you. If you are trying to fight underfitting and if you have regularization added one way of reducing underfitting is by we can reduce lambda to fix. So, once we once we reduce lambda what will happen is that we apply lesser penalty for model complexity and that gives us more room or that gives us more capacity to learn the training data and that is how we can fix the underfitting problem. So, these are these are the broad ways in which you can fix up your underfitting and overfitting problem and in your training. So, whenever you are training machine learning model you will often come you will often come across issues like underfitting and overfitting and these are some of the strategies in which you can fix those problem. So, we have two levers here. So, we have problem which is underfitting and we have overfitting. So, we have two problems and what levers we have we have we say more data more complexity. So, we say that more data does not help here it definitely helps here more complexity is by decreasing lambda and here we increase lambda and lambda helps us to. So, increasing lambda helps us to leads to less complexity more complex model more complex in terms of number of parameters. So, this is this is a summary of the whole discussion that we are having. So, this is a summary of the whole discussion that we had on diagnosing the problems with the model and fixing them with more data or more complexity. So, after we perform regularization what we do is we essentially get a model and we can run that model on the test data and report the performance on the test data which we hope will be similar to the performance that we expect on the future data and why do we why do we expect that because we make a crucial assumption that training data and test data comes from the same distribution. So, before we close this discussion let us quickly look at some of the evaluation measures so that we have good understanding of them. So, let us look at more of the classification measures like accuracy, precision, recall and so on. So, the first thing that we do is we actually build what is called as confusion matrix. So, confusion matrix is a key matrix from which we can derive all the matrix. So, this is let us say the actual and this is the predicted side.  If actual is plus 1 and predicted is plus 1 we have what is called as true positives. If actual is minus 1, predictor is minus 1 we have what is called as true negatives. If actual is plus 1, but predicted is minus 1 we have what is called as false negative. This is predicted negative falsely and this is false positive. Now, we will use this confusion matrix. So, what you can do is you can essentially apply so these measures are mainly calculated for classification and once you get a classification you can find out what are you can first fill up the confusion matrix and then based on that we can calculate measures like accuracy. So, we can calculate accuracy as so what is accurate which are accurate numbers which is true positives plus true negatives divided by true positives plus false negatives plus false positives plus true negatives. So, essentially it is a ratio of the diagonal element some of the diagonal element divided by all the cells in the matrix that is accuracy for you. Then we have other measures called so accuracy does not work on imbalanced dataset where there are too many examples of one class and too few examples of the other class. But accuracy works well on a balanced dataset if you have roughly equal number of positive and negative example accuracy works in those cases. So, in case of imbalanced datasets or in general we calculate a measure called precision. So, the precision is the ratio of true positives divided by total predicted positives. So, what are the total predicted positives these are true positives plus false positives these are total predicted positives. So, ratio of the actual positives to the total predicted positives is called precision recall on the other hand is the ratio of true positives to the total positives. So, what are total positives which is the total actual positives which is true positives plus false negative this is recall and we combine precision and recall into a score called F1 score which is harmonic mean of precision and recall and is calculated as 2 times precision into recall precision plus recall. So, these are the 4 measures that we mainly use to evaluate the models on a classification task. So, this brings us to the end of model evaluation discussion and this was the last piece in the machine learning pipeline. So, you know let us summarize or let us revisit the steps in machine learning pipeline. So, we have we start with data, data is the essential component of machine learning pipeline. We first do data pre-processing, after data pre-processing we build model. Model bringing involves specifying the architecture of the model or the model function itself. Then we train the model and then we do model selection which involves selecting model of right complexity and finally, we get the model on which we do predictions. So, we do prediction on the new data and we get the output. Note that in a single though we may not be able to get the final model. So, what we do is so, there might be a loop over here. So, we do training, we do model selection, we may not have good enough model, then we go back again, we recheck the feature see if we can add more features to the model and again repeat the process. We do this until we are satisfied with the model quality. Once we get the model of reasonable quality, we deploy that model and use it to get predictions on the new data. So, this is the entire machine learning machine learning flow. So, I would like to make a passing remark about the components in machine learning model. So, this is a very very important view of machine learning model. So, what happens is so, if you if anybody tells you that they have invented a new machine learning algorithm, you should ask them three questions. So, the first question is what is your model? What is the mathematical function in your model? What is your loss function? How do you calculate the loss? And third is how do you train the model? These are three core questions you should ask. In addition to that you can ask couple of more questions. One is what is your training data and how do you evaluate a model? What are the metric that you use for evaluation? So, if we ask these five questions, we will be able to understand the machine learning model pretty well. So, this is a componentized view of machine learning model. Let us take a concrete example and see how it how it goes. So, in case of regression, a notation where we use this x i y a pair where we have y i is a number. The model that we use is is b plus the linear combination of features and their respective weights. So, this is the model. The loss we use squared loss which was half, we calculate loss across all the points. We take the prediction minus the actual value, we square it and this is how we get loss and then we use gradient descent either batch or mini batch to optimize the loss and find the parameters and we use mean squared error on mean absolute error as evaluation measures. This was for regression. Let us try to get a similar view for logistic regression which is a classification algorithm. In case of logistic regression, our training data is again x i y a pair, but y i comes from some fixed values, let us say 0 1. y is either 0 or 1. Our model is essentially to take linear combination and apply sigmoid function on the linear combination that you get. This is our model. We use cross entropy loss and we can use either batch or mini batch gradient descent and we can evaluate the accuracy with precision. So, if you come across any new machine learning algorithm and if you ask this five pointed questions and note down what is really and note down the answers, you will be able to pretty much understand what is really happening in this machine learning algorithm. We are taking the training data. We are understanding what is the type of machine learning problem we are solving whether it is a regression problem or a classification problem. Then we are selecting a suitable model. We are defining a loss function and optimization algorithm to find out optimal parameters for which the loss is minimized and finally, we evaluated on suitable metric to report the performance on the test data which we hope to get also on the future data. In this process, getting the features of the features for the data, defining loss functions are activities that are tightly linked to the domain. So, hope you understood the machine learning the whole end to end machine learning flow. You had a good understanding of componentized view of machine learning model and also steps involved in machine learning pipeline. We will take these learnings neural network in one of the follow up sessions. After this session, we will go to neural network playground and understand each of these concepts visually which I think is a very very fun activity. Hope you enjoyed learning this part with us. Thank you.