Creating Linear Regression Model for Machine Learning in Hindi | Shiv Kumar | Skillshare

Creating Linear Regression Model for Machine Learning in Hindi

Shiv Kumar, Programmer & Data Scientist

Creating Linear Regression Model for Machine Learning in Hindi

Shiv Kumar, Programmer & Data Scientist

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11 Lessons (54m)
    • 1. Introduction

      1:14
    • 2. What is Machine Learning and its types

      10:47
    • 3. Difference Between ML and AI

      8:46
    • 4. Advantages of Machine Learning

      5:11
    • 5. Disadvantages of Machine Learning

      5:45
    • 6. What is Linear Regression

      7:22
    • 7. Prerequisite python numpy sklearn

      5:19
    • 8. Steps in Creating Machine Learnig Model

      3:43
    • 9. Introduction to Google Colab

      6:32
    • 10. Implementing Linear Regression for Prediction

      12:27
    • 11. Project Work Finding Regression Line and Conclusion

      6:23
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About This Class

In this class , I will teach about building Linear Regression Model in Machine Learning for prediction problems. Linear Regression is a supervised machine learning algorithm where the predicted output is continuous and has a constant slope. It's used to predict values within a continuous range, (e.g. sales, price) rather than trying to classify them into categories (e.g. cat, dog). 

Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so.

And, linear regression is one of the most popular regression technique used in machine learning. 

In this class I will cover the topics:

  • Introduction
  • What is Linear Regression?
  • Python numpy sklearn
  • Steps in Creating Linear Regression Model
  • Introduction to Google Colab
  • Implementing Linear Regression for Prediction
  • Project Work Finding Regression Line and Conclusion

After finishing this class, students will be able to work on machine learning problems which requires Linear Regression model for prediction.

Who should join this class:

  • Students aspire to become Data Scientist
  • Software Engineers 
  • Data Analysts
  • Junior Data Scientists
  • Anyone aspire to learn machine learning and its models

Pre-requisite for the class:

  • Basic Understanding of Python Programming
  • Basics of Machine Learning and Data Science
  • Interested to be part of Data Science Ecosystem

Meet Your Teacher

Teacher Profile Image

Shiv Kumar

Programmer & Data Scientist

Teacher

Hello, I'm Shiv Kumar. Programmer by profession and also by nature. I have worked for more than 10 years in IT and software industry. I am here to share my expertise and knowledge.

See full profile

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Transcripts

1. Introduction: Government will say commodity on map is running along linear regression, machine learning Kelly or classical planning and a. Q such ammonia bianco jhanas are oriented many passe. Thus talc experienced data science, machine learning software development become Guernica is class-wide map called linear regression. Kibera may put either because it battalion wallah who is classmate, this mayhem Hindi imagining Achilles, regressing Calcutta, machine learning-based Comcast. You, which cuts up the GAR was tips age is Kusama Porlock And now with a linear regression model, create clinically or hm, project during each one ASA, just ma'am, Dunning efficacy hmm, lunatic listen, Coleridge Cauchy Hmm. Predicts and costs are TM, dataset lingo or white dataset linger or x-ray loo, k bases pair y, value Kook as separate colonize comic linear regression model bananas or the community Cassie, x with x conjugate basket, the handle, Why wreck value hm, Cassidy debt to get complete Tortosa class only one law, just me running genetic reason model, I'm Kasey credit contain machine learning. Calea though are going up interested throughout this class called drunkenly Jay. Thank you. 2. What is Machine Learning and its types: In this video, home Janning, ATM machine learning, or Cassie come, can you give me sick? Jana bought generally machine-learning kick ECB algorithms. Jackie is plasma HUM LOG linear regression. Kibana began to skip on him and machine learning Kazakh, I'm going to hit Escape basic understanding. Rihanna, E, J, Kelley John, Thank You. Machine Learning or IQ is Preclassic. I'm crap. I kept on thinking machine-learning, gas or limit worry about the technical term lock the head looking, escape automatic system or gentle your body. The axon, a concept is the article home-based Amal, me liga, hey, hey, I see pre-calc key learning process head is making machine. Could, he boasts CTG, basically the hey, we now say explicitly programmed key, where the key I got up me, can we software programming keyhole, Java, python may see me or C plus, plus messes up me. The upbringing, I now got a point. We saw prep, canonical hammer police say he had ecological economics, ag, software, software, consequently scientific got Canada, cow opsins only Archie's Preclassic calculations. Okay, so explicit programming, hammock, holistic or new part, the hair look in machine learning. Us Army hotel. Hey, yeah, happy machine learning process through data. Hold them neck is Mickey data at the hay and S If you are so not that the war badly, Gai, gai, draw, learning processor was kept bases pair up inexperienced Casey spade. Or third day the higher fare steps later. Hey, so yay. Pre-calc application nota, hair, artificial intelligence, car door system. Cool, yay. Sucked deeper than carta has ability for the uncle that you say well, automatically up inexperienced, the HI, long career or apnea, go improved caret. So you basically karaoke, just see human draw the head will come up, new experiences can be split up. My intelligence cases become quite there. So yeah, happy machine, Coby as a program Bobby ache, artificial intelligence score, develop caret or could, uh, he, Joby data from low fluid cannot escape bases pair up like learning process, develop caret or NADH into their vitals. Case up, say walk, sit your son bed reactor 80 based on Jessica Humira, human mind, your hairball neural networks have been our health harm upon experience capacity specific turkey is a ceramic acid yet can now reciprocally GAVI, I can learning process gets through data Hammerstein or disable the hymn, machine learning. Yeah, Iike artificial intelligence score, develop gotta head. So limit. Yeah, but yeah, Ballet MOOC in analogous, such Okey, dokey article, artificial intelligence. It's not data at once organic machine School as it Bahasa com can ask. Thank you. Hayley Hammurabi sorts, renames up the tape. Machine learning, say dynamic environment for him, multi-dimensional, multi variety data across honestly handle, carry a flat tire, easily escape to save a polygenic, we save a polygon carry problem. Garden asks Abby, CALEA, Rudy here I got up machine learning where I can knock out. They had thought machine learning as the Hidalgo advantages. Hey, the key hung up on it. Any Cairo, Mr. Mom, a lot. They hang easily arch machine-learning AI or they're Catholic anchor tag command image, I'm Kelly. Prompt getting a or is a better fit someone and they may suddenly hobby, thought at least circuit, Thank You. Machine Learning. Gao Hey, machine-learning, yes. Yeah, but dark application or artificial intelligence, cargo systems, cordiality per cup the heck. You save automatically launch casa killed or upon HIPAA, go improvised car suck. They are improved or camera with every girl prop cut, basically a second Nick and warp and experience. Could he come a lot their hand NAPQI, explicitly programmed key I gotta hey, machine-learning Komisar computer program. Kw say what data could access cursor kid or bottleneck could keep learning. Kelly's the MLC or saccade is me learning data key observation is cargo process and muscular Nika. What data object responses to row tire without actually are going to have direct experiencia instructs son data impact on Kadoorie, gaba. Wish everybody a traditional enemy. Object recent get through. Carter Ham, machine-learning Kabuki, lucky. Guess the computer automatically long career or inaccuracy human intervention. Yeah, system K, the sticky war operate excellence was he's upset, I've just got to keep up machine-learning algorithm kick it, apricot, hold the thing. Machine-learning algorithm, Kwok circus category me back, I gotta head. Jellies can be similar auto script. I pretty much jumped to him. So subsequent LIGO machine learning algorithm, our second they had supervised machine learning algorithm. Yannick ERP, machine code supervised Kenyatta who said, but I got the hockey, he got a dog. The kind of kind of a thing just by freed care to how to feel more CMO still not cut the hay. Though supervised machine learning algorithm, algorithm in Mozilla, machine apnea past my joke OC cow that we'll see Econet it up like Arthur has the symbol labeled example, just document AKA hockey, cat or dog. I'm going to multiply foretold hat or hum, level cardiac equally photo cat key, Hey, you only photo doc or keep receipts famous income training then get supervised training, cafes it or feel hm EQ. And therefore to introduce getting it to do, we launched our wacky cat cough photo cast out, our doc offer took us out. I'll skip it. This will predict Gallagher. And now what do four per head will get Gaia doc, I see supervised learning. Cut the head. Yeah, happy hmm. Labeling data. Get through Moscow. Train cart. The Odyssey is a super wide machine learning algorithm. Cut the heme is my IQ normal painting. Let us say if k, a good learning algorithm egg per car inferred on some pilocarpine, a joke, Yes, Annie, separate exons, casa, output values. Can we say me just like you whenever that cat or dog. Go predict condemning system PCB name put Kelly target provide card stock the year when it's sufficient trim. The Naipaul yay learning algorithm, we neglect the output. Go compare, got the correct intended output, gesagt error, square root, THE stickier model. We'll see he subsidy modified casa. Okay, you happy I'm ubiquity output. Prop got the handles, go home, locked door, desired output o say mosquito law cartel, they take us, make it an I or kidnap percentage, homology or machine-learning model. I'm going to walk you through that person. So he pay autoscaled receipts for HMO setup or modify cup the area or regional training that they're almost K50 CNC autoscale data, hey, yeah, feed Joe's key Innerscope. Come cut the hand autoscale. Good to see you and it gets to the Dakota. Perhaps they hang dorsolateral machine-learning algorithm. Oh sick at the unsupervised machine learning, supervised machine learning algorithm is an algorithm customers don't care the hijab information to say trim kit, GI night classified O nine level or Yannick? Yeah, happy hump support, Schicchi, cat or dog graphic. Just say like in rpm, one single unit with ikea get Gaia, your doc, I have rpm labeling, getting a rapid classify the heat, getting good data called unsupervised learning. Yesterday got the Ag Cassie system QC functional forecasts are Cage is the unlabeled data sick. You see she didn't structure could describe classical ERP data, um, machine code that they had record but could the site curve the Heikki can see category Mick Jagger, Yeah, we'll do categorization operate. I have a machine learning course, Ceylon Kirkegaard tiger system can see right down output coordinating describe curves, the licking a Data Explorer cacti here or it could datasets in forensic drucker THE sticky he didn't structural core describe Kawasaki unlabeled data schema the same. The slipper cargo machine-learning algorithm. I was sick at this semi-supervised machine landa don't know supervised or unsupervised learning K, middle key bath, hey, Yankee beach cutoffs the heck, Tsukiji don't know labeled or unlabeled data to estimate the Jacobian blue label data with unlabeled data would they felt was kept bug, was algorithm kwame looked train cart, the hand model, kilohm Lu, training, the hymn, typically dokey, Who the heck is small amount of label data out there or large amount of unlabeled it out. I'm good with just feeling achy. A cat, cow or your boss or a prick tests ascending or just make wavy label name pump but angular system could, could decide category, key, concept, cat or dog. So you see it get this semi supervised machine learning. You happy I'm Bobby neck, your cat guy at aka here. For our input there, the authority hinder the oldest cave are several cookbook would decide cut the hair. Well, system code is jokey, is Mr. method guys to malloc the hair color, body as Sahni say, considerably learning accuracy, improved course octane. Usually say me, some supervised learning could teach kids at the hijab labeled data package or growth of the hair, or skill or relevant resources, ie, you say, okay, trim costs again, once a week or so. K on the top, unlabeled data, quark or Nikoli, additional resources, Keyczar within the heme hold the hair to calculate your learning. Have pores, machine learning and key reinforcement machine learning algorithm. Yeah, Apricot can learning method head Rookie whose care environment gesagt indirect cut the hair excellent, produce gut or sati adders or the wordCode discovered we cut the hair trailer, either search or delayed reward. Usa be most relevant characteristics had in post-print learning kale, yeah, My turn machines or software agent or allow Carta automatically PCB ideal behavior according to remind clinically, your QC specific contexts can be thorough or just say, yea on key performance called maximized cursor cave. Simple reward feedback. Both the Jody or the heck PCB agent CALEA, Just take a LAN cursor KCI on Cx and best help you learn cursor KCI called CX and best here, odd is equal reinforcement signal because Data him machine-learning in massive quantities. Beta, CPU and light scatter the head, dehaze generally faster deliver Carta, Hey Jack, good at regional. Just say yet, but they're like I just said, thank you. Kate Harper property well, our possibilities here. Yeah. Harpy badaga risk, SRP me, it's me. Additional. Our time or resources be lux up the hand. Just say in a severe groups it properly trained care, that's okay. It must occur in Guernica. So tacky, I gotta machine-learning. Ai or cognitive technology could start combined card. They thought you said java, effective that he gets a large volume of information, could process good. 3. Difference Between ML and AI: So pitch the lecture may have made anarchy, machine-learning care hotels kick gap, pericardial thing. Or I'm the guy, lucky machine-learning Cato, regard hand Jessica, supervised unsupervised learning and reinforcement learning or semi supervised learning environment harmony. A brief Madonna upon that, the Hickey, artificial intelligence or machine learning way, cow, coffee, sorry, local attack artificial intelligence. He machine learning AI and machine learning artificial intelligence. A Garfield, No, No Coffee, lucky Jahan. So map cope with Auto Key, EQ, umbrella term here, where data science. So data science, a umbrella. Machine learning, artificial intelligence and deep learning. Yes, our HER, the hand on machine learning or artificial intelligence. Don't know the exact milk AECOM Capital X is to monitor her door, human intelligence score, simulate car septa. Here. What you see in machine learning or artificial intelligence score X sub collaborate card k hump, basale, TGA, or keep constructor here are human like distance, lays out the ham. So machine-learning, just a camera Jackie, machine-learning karaoke, machine code, Cassie hmm, data, get through, train caret, Cassius, Clay and that human type experienced develop Corita keyword. This is Jen could say lists, okay, I got going Nair type experience are the highest secure sonata. Hey, yeah, peers connect. I put it Hamilton. So based on the previous training, WHO's Chios Kore training will use kept business but what gas it, it can add the stem less a telescope. Machine-learning cut the hand. You can machine whopping, LON-CAPA could buckle or lead is useless, dire. Artificial intelligence, Caltech, ERP, humped software, give that account, got the happy. I'm low. Human intelligence could simulate connected courses, cut their program chronic equals discard their auto-scale based intelligence developed machine Canada, the sticky work. But that costs okay, they will all die. I smartly conquest of time. So Lichter, ma'am, Dunning, still intelligence or machine learning, we got on that head. So subsequently MakerBot dot Duke in machine learning, apricot aka feature head, you see experiences, knowledge or skill quick Qualcomm, high-energy machine-learning K, learning process, just the hum, human lung Curtin, where same machine, we learn Carta heck acid, which will say data or data bases. Famous encourage LON-CAPA here is typed. Got eight ahead TO each type. Got it. I had OUT yoga, always skill or knowledge or fill the metadata, the the handle so well. But other Hickey, guess it would be silly satire. What he paid your artificial intelligence a darpa intelligence score defined as the ability to happen knowledge and ability to happen Knowledge go acquired or apply cat the enemy machine learning through him long knowledge or skill to acquire, cut the hay, or artificial intelligence cut-through hm, was acquired qt and knowledge or skill quo apply Carter him, ticket. Machine learning in Canada hit UCB. This Genki accuracy Khurana, audience successful gathered hand me that I could just say key. I got him quote, task array of your image. Classification kinda gonna counter dot-com, longer machine-learning come in with decidual Diebold. Thank you. Guessed the hum it picture called 90 percent, 96 percent, 99 percent accuracy or cheap? Yeah. Jackie cat Catholic kilogram system chordata will copy, but I hope machine learning come window, additional DI water. It could SQL banana and make it machine learning models come I said Bianca, take a look. We've got this yada, It could attempt, correct? We'll hop is success. Penny, the air that then I've got a 9%, but are they hokey Godhead will appear, Jacqueline only, but I don't know KitKat, the heat. Okay. I Berlucchi, 99 percent luxury. Yeah. Right. I B being equal to a 100 percent yeah, cat here. Happy machine-learning accuracy be gathered. Top of the head. Nikita success bit where he bid or artificial intelligence. Door, mental disorder wore their hair. Accuracy called banana accuracy equal number 100, bulky, chance go bananas, success, Khurana, starting Priscilla and billions gag up their war is mark the gala door door that the heavy hump. I've got image classification current, I had to go home, look, Cassie, successful been I I got each and every time I got a cat, a cat, a heap, but I lucky 99 percent bulky, 100 percent accurate. So artificial intelligence make them look success together door that there are machine learning may accuracy score perhaps they had I've got my printer machine learning Quito muscle in Quito machine learning, simple concept, Massimino, tf dot data, Lithium auto Ceylon, cochlea just documented Pali, but the key data he's a co-chair, machine learning and data science will make odyssey lay score data science can take glucose stock, which a data car. He ERP game here. Data EKG machine called a hint of what was the data get through boss study, Quito, cool. Ct, hit auto, say he walked long Cartier who see a pretty sensibility here. The empty artificial intelligence can, it can protect program, just say conquered, odd, geek, easy ComCo or data cache. It smartly gets split data your hotel machine-learning, Godot. Just take a minute, but every time when this edge we have wacky gassy IQ particular task C and data get through the other lung cancer or Muslim key performance go up to the group say Baja, the idea is, if you see it Dusko canonically weight back the President anions come in glucagon. Intelligence Copan I anarchy human-like intelligence. Copan, our human like predicts sunken knocking one like this gel Lena, human-like, complex problem. Coast salt, Kentucky jumped up except artificial intelligence can mean who does she have? Artificial intelligence could set is generally adaptive machine learning Calcutta, Quito data who say D Again, just say what training Liao. Well, we'll skip to just see the hair or to skip it says p, which we decision yuppies predict some data here. On machine-learning, khaki, machine-learning, Dove, soap learning algorithm page either walk up the heap, artificial intelligence. It's time to develop Carter, Hey, you're in Fano K Intelligence. Go McCarty had Jessica in some situations may allow electronic acceptor yet cut the hair because that is spawn got the head seat that I say hmmm system Question their blood potassium mimic cartilaginous code is CALEA he happy to have artificial neural network, I'll say artificial intelligence by Joe, human mind can stimulate Carta one artificial human intelligence to hang in one mind majo, neural network that was go home look artificially, system, get through, simulate can ecosystem cartel will say artificial neural network cut the hymn, or it was kept busy, it's pumped same human-like my son ME machine. Yeah. Artificial intelligence system, gassy and respond to that. It was pick out the door or the hair. Eia, homosexuality problem, door hold that. Optimal result. Tortilla solution or tau scrutiny. Key courses, catastrophe machine learning, solution, key accuracy, photography, and goddamn day 10, knock you optimal solution door neighbor. Machine learning, knowledge or none input data door that the hijab characterised UCL intelligence, intelligence or wisdom. The wisdom that up Jada is called ricotta, hey, that you're happy up ECMO, token machine learning to help what gathered your data heavy jacket, this is b, hm, it must include Cassie hump, feed costs up the heck is secure. Send me GIS data set the icon now API key for the silane diligence come in with this EA you in one lake intelligence and develop cannot compute asthma, just kiss the sticky. Computers and machine learning are actively selling the exact Colab, collect, carry XR, collab, cornetto wouldn't all milky. Human-like decisions linearly, such somehow pay for a year die. Lecture remembering an AKI guests it hmm, machine learning or artificial intelligence game minute differences course, summer stock, the hair. 4. Advantages of Machine Learning: Weekly lecture may have no Jackie machine learning or artificial intelligence make gap and that hair or harmless and Jackie don't know me. Yes, I can differentiate because I don't really use ECOSOC milky gap Kemal costs of the hand. So it's resume haven't done any machine learning Kcat advantages. So machine-learning cables advantages are asked. We're going to have an identical manga online Kanyama it up or machine learning or are you still in, didn't skip a whole study at the Applications Technical Miliangos. So Balsari applications have, you can expect on me, I will banking, whore, health ghetto, publishing, whole industries or health care, or financial services or healthcare whole BFSI ego, hard to dig up or artificial intelligence or machine learning applications, technical metadata. I'm going up to succeed Ghana. Can he be a machine-learning Gao, use the formula to Google or Facebook. Gets he but he company, yeah, yeah, Jacobian machine-learning case, the multi a advertisements. July gotta head or yeast, that advertisement you get k drops, tachycardia and Facebook or Google searched, gave the heavier can. Either Pepco advocate at the Medici were really a peaceful play. Kissy company, kissy Greek evaluable watch cable animal starts to go up. They kinda kept book which recently about Facebook or Google, Apple Watch SE related ag economy. I've got opposite. Washing was thinking about him as such here Dr. Watson was insulated. Add on elevating are going up and they call it could be happening. The Hebrew apnea, housing get acetylated, got nakedly Macondo Nikoli a house do Nikoli 100 Nikoli up nickel, adequate realistic simulated annealing neutralism up you'll be warp activity Carter who was the DACA unhappy Google or Facebook. Up k exponent screen has gone. It seems that okay, Advertisement the cut edges sticking up or redevelopment, admiralty or do company Facebook capacity reaction unequally. War, we target audience Tecumseh at Poshmark the head. So yes, September I jump on Machine Learning, got Dolby data up such codeword data, Google or Facebook targeting elders kept the Harpic up, go add the economy on cosa was data coulda Harbor he wacko acts are Carter Ham, machine-learning customer, multi-dimensional on multi, when I did it a 100 chronically Giga or dynamic and warm and me, machine learning is thermal, say time cycle, really axon Ho Chi Minh, going to be crass can limit your time. Cosine calotype is about the time consumers are happy I got Bautista time bust the hair or resource efficiency you pledges and BC bar data, ionic app, resources. Got your pleasures and we're purchase a car part. They hope. I'll get up the COVID team machine learning, artificial intelligence yet deep learning car would be looked up. Go Article 3, OTT played palm this in Netflix, Amazon Prime videos. Youtube is probably up with a Geiger. Yes, icky movies recommendation up taking an eclipse path of Wolpe up, Kd, rude, cheeky supply going up or romantic movies they cannot pass on their top cool romantic movies. He lift up, go and recommend categoric, got up quite. Xn will respond on the Dakpo X-Men movies. I gotta go French movies person that Dr. Franks, MVC, you kinda gotta get past such as our apt-get pre-prints a scad hospital, Netflix, cardio, movie recommended recommendation system has EEG machine learning or coffee. But yeah, gumball where it gets hard, they can get a Google image or image search cops on the API will be ICA, our deep learning get coffee. But he had jumper layer. I'm going to Google search query. They can get the Wahhabi up. Oh, machine learning, artificial intelligence, a huge key. I gotta check off each other matters. I mean, ESA, happy machine learning or artificial intelligence Skype your care. That is key, sati, I'm going up the king is substantial, advanced measure children who have face recognition. That article COVID-19, kissy to synoptic albeit or mass ban area and a piano is got detect some clinically boss at applicants and monogamy is COVID 19 kid, or are you happy? I got up and the piston leap and I critically arche face mask. Here. You see it that our facial recognition, we Mozilla Nika example here, escape the Southeast or auto, auto autonomous cars to hair will be machine learning or deep learning AI, coffee on dot-dot-dot. Hey, Becky up. Self-driving cars or driver nibble, keep a computer car Ctrl arrow here to, we're happy we copy Sarah data feed, coffee said algorithm, tell it, I just skip it this way. Or human-like decisions, Labor Act, Corpus signal a CAB Abstracts and Santa Ana car could could push ten tons later. Here breaks up my career though, yes, I like TGA to have war machine learning came through he possible hope barrier three years iraq, which advantages they are uses the copy machine learning artificial intelligence or BI planning algorithms scalp your Kirklin insanity to court you yeah. Data. 5. Disadvantages of Machine Learning: Last video, my main Jackie machine-learning advantages is lecture ma'am, planning AKI machine-learning KitKat advantages. The machine-learning T, mainly char disadvantages. Just go home, look, charge our category mm bolts at the Bellagio Hercy high up. Such susceptibility or their data equity, sunny, disadvantage or rituals could interpret it, interpret Carthage, interpretation of results. Disadvantaged. Or her what time or resource casual. Iq. Bobby said one day, say, I'm done with the heck him detained, making my data all the machine learning type groups of zebra joe problem, hey, yeah, field limitation, a wacky data equities and you can machine learning. And you start out your algorithm, Hey, I'm machine-learning, model trained care thing to algorithms. When I got the more subculture data to a different cut that or not. But he had a tautology. Not gather data or not. I'm putting up a modal, cutting out OData equity cynic. But our challenge, machine learning may or to Kosaraju algorithm or to have all the data. You see KPC scribble, process guy at the head. So respect to algorithm per process carried out east come body Jarrod, significant impact or the head recharge slow, but Joham, machine learning algorithm gets worse. You've got the hippo data equity sonic Birra problem, hey, or data quality son Keith LA, Chicago, machine learning with 19 per year per pumpkin regard. Those are Dominique AKI, interpretation of results to be a problem heck UP. Bad but are chattering, shaky is still determined can now thank you. Machine-learning algorithm key effectiveness can, um, do is exert telescope, Parkway electric is interpret cursor back. So happy. Cassie, up, interpret cortico up CARTO. Knowledge here was trilled images, will keep key data co-op analytes, cosine oh yeah, do predicts, encourages PMOS. Current knowledge. Guy was glibc scheduled machine-learning algorithm, gas interpret CTO, spray bottle, which a print cut the hippo data, your result interpretation there will be a limitation machine-learning CALEA. Machine-learning casual users have a limited overhead or so per year we bought the other austerity name or Tiki homicide to how many imagine, yeah, hey, machine learning algorithms or trained cartel, way uptake got the weight. Yeah, Joe Homais, door protesting Catherine firewall, blocks and around us I got a digital camera. They can accumulate ciliate the high-tech EEG data, machine learning algorithms or models or they have a failure, nothing. Or UK who spoke out. For us, our budget changes a, a thorough savvy data, job, omri, past data, huge new data. Sybil could be unrelated either to a machine-learning ago. Digital dynamic problem with your reserve went up or down soccer, yeah, hobby. Yeah, a machine-learning disadvantage in deep learning, major CQI, our training time doth ever bought each other. Wacky machine learning where we don't training time, have word data or data. Yada, yada. To training, hold your time. Be less eager to gather. Data is outcome cannot be hold up. I know you're happy. Data gathered, your data gets outcome can now is going to be, it can be at equilibrium limitation Embassy in London. Got it. Bowtie are notable. Limit is LMS inland inky key areas at the hip. It was kept pretty machine-learning bodies susceptible overhead, or go home look errors, pay data. The only the term Innerscope come connected courses. So Harvey, say diagnose cannot occur, it cannot contain WHO data heck, Mosaddegh cases me, Yuki. Mosaddegh cases me, Yuki was draw me modally. Adobe algorithm includes cows to underlying the complexity and maths. It was some multi complex or the heart or through other can you bought Zara impact? Does it ahead. So you take a limitation, have machine learning car or immediate t0 possibility come with the silicon immediate predict cells TO machine learning system. Qsr was bulimic historical data, so we had lunch or something. Go previous dataset was a machine-learning non-cardiac or anybody you OD, machine learning algorithm. Oh, status, data coords or the exposure malaria, licking your problem. You'd be at the Akira Iraq Asara data machine learning training may also feel who bought the accurate predictions than enough the heck you cuz causality talk about empathy. Though, you're happy we hammered the unmet acknowledge that a data for machine learning model to export and knock on equity data, Asilomar, Mr, painting or atomic split carbohydrate distinct it out that or training data to start to encourage the hair out. Which part? Yes. Or 20 percent QSR complaining authority person cannot discard the end, you stick iambic. But actually like Yamato models get an accurate head. So ha, ha, data machine learning model to export or ghetto hump, a 100 percent accuracy. The 100 legacy archaic smile or walk boss or a production environment, my body. Because then you'll have your machine-learning algorithm doesn't focus is my fail on a lucky guy or Java variability can now hone our limitation him machine learning. 6. What is Linear Regression: Take references. One is classmate or intellectual man Dan and Jay can linear regression only in 100 precent Kwame copy which contain or they can accumulate, regress unquote Cassie, Python port cut-through implement concept. The HC, DC keys k1, MF predicts and condemning, yeah, Nicki protocol dependent variable. It can take men and 20 Wolcott change on a path toward those subsequently analytical integration of attack, regression, statistical modelling method metallic, this Mia Hamm regress analysis container yet but I can Nikoli key eq dependent variable or it dependent variable, dependent or independent variable habituate catalysts and say Yannick independent variable edges Kwame log bot attack, outcome variable, Catania dependent variable can look. Outcome variable, Yeah, Nikki Joe Hamid, prompt hotel. Whenever I love everybody and final output melt I was calm. Look outcome variable or dependent variable, voltage. Dependent variable is labeled the two key independent variable, speed depend hotel, Hey, Joe, predictors Jacobi, yes, yeah, features bolt and you can just have so much to geeky up. God your company up. Suppose applique complete and Carter company may propagate your loss. Yaphet Duke who's got annual revenue on a monthly or quarterly revenue whenever it will. Sadducee GOP, depending on that rate, will depend gotta cap kidneys and ready to hand opcode profit kit. Now, Colossus get nota, apt-get expenses could write you Balsari TOP upcountry when you do help distribute, decide can never leave factors yet. Feet just say independent variables, voltaic, UK, eco-cities perpendicular the leaking, do revenue here. Well, our enthalpy independent variables just Nikki implies salary. Yeah, feed up, got profit loss, yeah, upkeep expenses, insanity, GOP, depend Carter, outcome had your revenue house kilohm load dependent variable multiple linear regression estimator has this kid through homeopathic Yankee in dependent or independent variable, may God really sensitive play or ISI liaise called linear regressing can take yuki, job come dependent or independent variables can be quite a big linear group. Tala, hotel had he listens to port, I have to say I'm logged, linear regression. Catherine ham, or is it just the capitalist state linkage to some the call got delta wij Col2 and mx plus c, you happy? Or Waikato. Do power have will came easily to clear power, you'll have one hastily say, linear regression Volta him. I've got power is quite mosaic. Cuba has, that'll give it garb, Hodeidah, do you linear equus and nucleic, straight-line new bubble kick, Garbo dagger drama, glass-like McNeil and I guess the key is updated every happy happy to exit or year. Yes. Xx is by how many x values plot or y axis, the y value. Yeah, happy exit. You have warhead independent variable X k where loopy Hamlet, wipe predict correct, right. Support key width or height, k, Sundaram, Milgram, they can't. Exhale, will wait. We've got QC Vertica or wide yoga, height or a yap it up as a techie, height or weight Godot, to really listen to their voice. Empedocles octane or like a completed profit or loss pay Hamlet, who's gotta When you decide costs octahedral, yeah, happy ego, point. Say, yea. Well hmm, it, but I can knit inside points k beat me XOR y, we're looking between a mic, linear decreasing model, banana hotel had to, yeah, happy homology or linear regression model calculator, you happy, straight-line find Canada jokey. It. Hedonic x, y politically. Or he, why'd you walk in July in Hami prompt or ECM look, regression line voltage, RDA, straight-line, Hotez Lee, I'm Lucy. Simple linear regression be bolted TO HUM, LOG, yea, yea, getting Ag, solid data points. Somebody on God is CAPM model, but I do make Nehru alluding to Hami x-value rolling it or my y corresponding y, it predict car category. Or x or y, Cajal, equus and alkalemia Nieto colorblind is Tanaka result with this at time rate. So linear degrees and Kudu equation, Hanwu, straight-line cake with some caveats I otitis, a straight-line occupy Y equal to m x plus c. So Linear Regression Chi percent v y is equal to MX plus B plus i, e plus bx. You happy? Erb, Yap, presumably I'm Joham. Okay. What constant, whatever disabled or PCM's. Yeah, happy to have our interceptor intercepts. Diego. Ya think at this point come later. Yeah, Hathi. X-axis. Ok. Are you happy to intercept kalguksu? Diego lentil tie is able to have or do you just slope? Slope, angle, AOC unlock emboldened, right? So what c or m to c and when I say E or B to have regression coefficient voltage dependent variable, y, predict cutting it on X2 Omega passe, or the predicates over E or BY looking versus pay, your BK constraint had been ham or present Voltaire, yeah, peer coefficent optic lesson bolted jam linear regression model of an angry thought linear regression model, indoor value scores, predict categories can be split, is equus and memory ALU doll k, y, y1, NewCo Asana is pretty combining. Yes, SEX tiling of assembler semi YOU element doesn't have an x, y pair been laggards get through and logic predicts some line decide construct the hand to linear degress in Kibera may get clearer. Jag opcode Javan looks and says I'm cutting it. Python, Matlab, cochlear or deck as Dambisa, carbine gay. Up, linear regression. Linear regression. Predict sun, Yeah, forecasting may usual digest that Kim and ABACABA diarchy, height k versus belt width predict costs or yeah, pin up Cassie. Does it get called Berlusconi 1D and the only way we'll Sadducee job, they listen, cut-through, podcast construct the hand. Or dependent or independent variables can be 20 lessons. It stop it connected levy. Huge caveat. Yeah. So I'm ugly. Lecture media, happy. Linear regression code Python program. You get three implement Cauchy. They can get out Hamlet, which credit card given the kinect camera prediction values at the end. 7. Prerequisite python numpy sklearn: So Hamlet richly lecture me the Cauchy, linearly crescent Carlota, kinetic lesson. Cassie, straightlining question, Coppola cacti whites called m x plus c job family, nana, keep war. Yeah, wij equal to E plus Bx, Bx plus a nap. And we are lucky to have interceptor or b coefficient array to EOB Clicquot presenter. Yeah, constant like a scary crescent, good. Doing coca Voltaire Co-op Centre, regression or ERB where lookup basis behind log x, e or Weka visit pamela white predict obtained right for years. Similarly straightlining notional diagram, we're gonna Mhm jack on newer lithium logo near hmm, low IQ linear regression model cuz you can get distributed spam looked. Pretty cutting edge. Okay? But linear regression could implement kinda polemic pushed TJ prerequisites bedrock, honesty. Was, was it valid? Your teacher will have Python programming language to Python programming language KaiC, high-level programming language head to our quantity. Or I got up to about began and he began to hit up the squeaked by Jackie. A basic understanding of the IGY bucket. A program may huge columnar warm apple, but others are longer to Python. That would be a machine-learning CALEA, UK subsidiary, popular programming languages. And enough machine learning, deep learning, artificial intelligence. By knockout the enthalpy does have, had NumPy, NumPy library, hey, yea, and demonstrate arithmetically huge chaos bacteria. Deja, by autonomy, inbuilt Aereo tile licking, NumPy, library headroom. Python may module that just comm loop item huge constructor and demonstrate at each go support Qatar or diego by Tanaka enrolled at a housekeeper Lama apologia fashionable to have border that convenient or that huge. The upper machine-learning when numpy and it got bought data use automaton NumPy. I'm logo, which can only happen. A programmer is good law ham looks like London machine learning Geico package is calm. You can scikit-learn odd East major scale on Weibull det a yam, which can engage scikit-learn coal classification problems can become huge, cut the hay. Psychic Lancome local regression problems can be huge Content API that's I can multiply it by liquid discuss together, can execute this for YUM looked pretty cut to him. The topic continuous radical break can Nicollet exists and which can give me up demand relax after him. Thesis strategic clustering problems can be unlocked. Scikit-learn package sky, which cuts the hetero classification, whole gadget, sticky, male-female, profit, lost mother, happy home, key, gioco, it, ghetto, cataclysmic, classify Cortana WE OPM contain classic resembles a classification problem. That's a key email Hogarth for email modality can be spam detection, gotta hacky consignment, spammy. Once I email, buddy, I played. Though spam email direct cannot quit classification. Spam true or false. Is Pam Haryana DO categories over a two-way classification problem where this image recognition or gagega, human cafe say yeah, and he multiphase a dog, a cat. Classic weekend, Sunday autosome looks, classification problems. Well, they're machine-learning. May SVM, to her name was order an impoverished Yes. I say algorithm edges come look, machine-learning which cut the head classification problem. Luckily, Jessica multiple linear regression, the classical era Hitler linear degradation. Calea concerned multiprocessor applications. And then secondly, never guess and MapQuest sector just to keep the stock prices cooperated connecting the navigation problem and drug response drug, drug Jessica be Colonna vaccine, Tish Peoria to Cologne, Aki vaccine. God responds. The upto a two-way data. What are good or bad? May you ECOSOC dental drug, guttural response it, we'll be homologue of the Crescent get through, predict comes to him or skeletal algorithms and more cones can say, hey, as v-out in Yiddish, Polish to nearest neighbor sailed an impoverished, we think there's some really huge gasoline, diesel fuel problem with clustering problem. Yup it automatic. Group get the similar object going to say it's just a cap is imaged with the exact same ERP. Yet clusters been eig, a look-alike plasma technology does say tomorrow they can Gillespie Joe decagon awake similar objects and wakes up cluster k clusters. But the scope clustering problem will tell you happy gaming but are popular. Algorithm hemozoin loving way. Clustering algorithm behind Lincoln came in multip Jada popular. Classically, if somebody gets on our clustering, Gangetic yoga or scikit-learn library and machine-learning. Calea, huge key aspect here, scikit-learn core diamonds, nullity, reduction, CALEA model selection can be a preprocessing, can be huge. Carry out that, right? So yes, I think Egypt, oh, I've listed lecture Madame hands on continually. Get R3 phony. Okay, so dilemma to him next six and my job next lecture, media happy I'm low hands on cutting edge linear degrees and pay. 8. Steps in Creating Machine Learnig Model: So it's like tell me, I'm goning geeky linear Dick, listen. Listen. Could implement connect limbic. Steps, follow, can show subsidy to Hamada, boss sensibility, don't IT? Hump but realistic Miami-Dade acre taco null data or data preprocess cannot already that would transform can now that I think is a porch gap capacity, high dot, ups company said illiterate, good revenue related data hit the wabe, Celtic support, the quiz points missing what they can see. The portrait you see him play curriculum, missing a Jacquard, kissy months got ever knew missing a yak which Profit and Loss connect up, missing the course data, missing whole thing about becoming larger than what I've written with that of course, went wrong. Voltaic, which were missing. Values, Guam luck, data preprocessing mate, yeah, our transformation misconfigured. Got dental school to exploratory data analysis. Still happy. I'm no good alkaline lakes cartel to V problems. So small tears come look fixed Cafe attack, India dot data_jags, Scalia, ugly processing, gliadin model may you, which can make a little happy. I'm looking at the key supports, key up capacity, hydrated data, hardcopy. Would you just get a height? Yeah. We're missing half of them get an achy Yamanaka. Who's convened, tickling your happy, you average value, Draghi, Hamm Joy, missing values, young girls, Pembroke, evidentiary logo, put carding, it'll be seen Omar dataset completely negative IQ that aka our data fixing or gay or data preparation hogan Yeah, data transformation, Noria, gay home contain data preparation or data transformation. Stigma was cable and I'm logged in the lending listen Komodo or not, they are data driven by fossil telescope. Fixed cut the hair. What's model may tacky model dyadic OJ. Each job only willing to lose weight or height k categories you hit was called Hamada models so much that a patent monopoly escape out. I'm Luke modal way to Joel. Score protocol, tangible kit life ECN tells me to skip coefficient value has disempower livable, kidnapped it was k by them look, modern drama at the airway. Taste can predict, got the hint. Nehru and watched ikea relevant l k. So you're happy, I'm lookup dished. Got the Hindi Dakota, Tama up, nobody say permissive print DAT 80%, um, look, training, 20%, texting Kolisch quartet or testing the deck is other modern goal dish cartel taking about it predicts and my looks. Yeah. The drain hole, yeah. Tom Luca cutting inadequacy pose Kwame, look, based got there. The whopping, I'm Joe, 20% didn't want to, but our dot density that was Cybil see spam look is model may wish to re-look or Flipkart extra lookup it Qatar, why we allude to Hamada predictable cathodes conducting. We'll get our ducks. I, I, though Yahoo gap would I process machine learning regularly? Some Yamasaki learning process may not go with Jackie data preprocessing the leaky modelling caissons delegate, pasting, dished split select model predicts some typecast them. Got to him along gag on new undertaking, a happy home look. Orderly can go only not aggression model, coin play mentoring. Though, yam, contain next lecture me. Explain calculate ING what I'll call putting someone magic up linear regression model. Kathie implement goes like the hat by autonomy or the happy I'm low NumPy, scikit-learn guys Killen, linear modal, huge carrying it or you're happy, I'm Luke NumPy adequately, which cutting it. So ugly. Lecture my gap em and some Carnevale. 9. Introduction to Google Colab: So it's like tell me I'm lonely Nicholas and go implement current Joham. Look proper chord licking your linear regression model, coconut cutting corners, get room looks Core present, Vergara paddock, an NGO or sat me. Hmm. Why where lookup pretty cocky. They can get their hands on system Honeywell ag or it's ma'am, load linear regression model go implement can engage or is Gideon may use Google colab. So Google collab, courageous or capillary tube provided not bad, good vitamins and Hauger duty, droopy done notebook of animism, alga, IQ, cloud-based development environment it by tonically machine learning collaborative deluge k2, where say hey Google Lee, lunch, GitHub collaborator tree, though google collab, Google Kuulab allow gotta hit Python or browser-based application, whether I'm gonna make a little Arabic, we, we hammer configuration connected closely, but again with Python called oxy download install connected with your Rodney, I'm logged just Google collapse Django and I'm look, ignored booklet getting, get Ottawa become locked direct biotin on machine learning. We are packages home logging, port collapse, I import car can block Lancaster AARP. We will collab hmmm editor, ghetto configuration, required, ubiquity becoming configure some connected yellow thing is a push-up. Go ahead Google collaborate, ERP, GPU and your head jokey machine learning course could implement connecting the coffee are important or the hair wore Hami free, accessible, tied UP May and it can check how say, machine learning programs to homogentisic temper uncollectible coffee, which some Alex attire will score. We have Coca-Cola patron costs octahedral gives you access to my freemium is already happy. Do up do we up the hill or Google colab notebook milk, they heard you Sqoop easily up Nicollet. Ksr took reference GitHub circles up the hills, cook it up. Maybe adults up there for you, happy. Derogate, vigorous and preexist for GPU on AgCl in Cops on Apple, Google colab, idea Jupiter, not book it that I, he did die happy hammock which connect the automatic I'm no Django order. Ignored booklet getting your lamp am look looks up there just to keep you happy up. Or typically getting already happy up, five plus four plus five, career are going up is quote, uncaring. Nine. They, they see you. So ERP, Python inbuilt data hierarchical, which become Nikki General. And the heap are the hair thick. Iap is seconds in a day up calculate career arc seconds in a day up print cutter to the rpm, just as quote unquote ingots are cool. The acting wicked dead seconds or there are cool. Now beta dagger, as I said, consider weak gig example the aware Google collab, gay base pay ERP data science may up, gets a huge cost of their world collab cohesive GRP. The, we have 400 giga Tegea are GLA hands on silicon as a polyhedral, be jumbled. The aware will go colab gave a plate be warm lobbying, well, it doesn't gotta get the click. Neither semi MOOC will collapse, which can name a kidney comfort level where you're happy the kidney does science, may have bootleg, Google colab. Harness the full power of popular Python libraries, bootleg, Google collaborate through upload Python libraries go, Asana is a huge cost up. They hold up my data to analyze ODE visualized cost up to him. What is meant by Turkey? Giga red item data, data can read carouse coffee, matplotlib, cutthroat visualize connector. Just like yup. Yup. It takes up doc ERP is co-author Matt Adam. I got output cathedral Diego. Orderly Kawahara is good Coulomb law. Yvonne getting atomic data visualization, Milligan thing and happy keg Iraqi. A numpy going portfolios can matplotlib code which can have visualizes some kinda huge oughta by blood or AGA PLT objects could use cutting-edge unhappy. Yes, 200 plus np dot random dot, Quran and a 100100 numbers core dendrite Gallagher, who's got the excellent Gallery X is equal to g x for x in range, or a 100 lent to me by use Gauss a_dagger, x-values, co-create calligraphy, two squared dx or YES, cool Ham looked plot Quran, auto, fill between hosts kilohm logging API. It can obtain energy, green color data, or freedom law. Plt.plot titled Irena's mother, graphite goes cold non-linearly of PLT dark, so say hmmm logo scrap costs, so cunning. So you have a plt.plot simply XOR y at Cisco, x dot y. Well, let's call it plane may XY plane, Drucker digger who's got the happy home load, which can be said if y yes, 195 metals come look green color than I am now. Happy. Why SQL Lu 19, five years from now, getting close to then get to get either five score 2.06. Yeah, for the o is called ulama run cutting it. Tomake visualize something I didn't kick, which we lose our cool blue medic railroad, Bucky green with ICA. The happy 19 P53 perky study, revolutionary happy. I'm getting cow gotta my school. Ricardo, or is coming from certain Coronado. Nikki app and read me Olga. To visualize an edge up and looked eagerly. Random data could generate k or P. Now P, xy plane pm login, it blocked QA. Matplotlib library call US turkey or Peter will hop amniotic face color equal to audio. Green, yellow, blue, yellow, yellow, divvy up color dimensional swapping, happy. They suck the hand. Essays, Israeli Colby up cadaverous at 10.9, getting into the queue count anatta is steady case upload is quite huge cost thing up, up, up naked opcode, hitting this Octavia Joby. Now I'm gonna tell you how they, SAM, look. I've got quartet can knock out 200 corporate click OK, accord that up. We'll skip Bosco to comment the natatio cuticle, somebody Nikoli, a key year data science. So you can drop quite happy, come into be Abdullah cocktail, ignored book eeta delta display, text on board except leaking out the hands to Yahoo. Google collapse like in production, Mhm login enhance onsets and predominate. Or finally, hmmm log-linear exists in Monaco implement cutting it ugly like January. 10. Implementing Linear Regression for Prediction: So pictured electromagnetic actually Google collapse or HAM lake simple program bead on Garcia Decca visualizer. Can they got Casimir? Is lecture mayhem luke, Final Project, can Joe, hey, x basis B x where looky VC's primary, why you expect where local predictor by law to subsequent religious coupled with the heck, yeah, me. Do we have a packages to leverage a warm import can now got this Gilliam import culling and NumPy, Duke am look multidimensional and is huge. Can you I'll hit on numpy Hemlock import. Numpy import clinically important space numpy as np. So you happy numpy as np huge cutting up MNI coordinate m, np dot carrying it or NumPy package 2py functions on Guam Lu easily which can do sludge of classical linear regression class to hm, link scikit library, say Scikit Learn, yeah, SKLearn library, cylinder to linear model package. I was so happy I'm learning linear mechanism Coby import can linger. So paella step yogic EM image will be liabilities say yeah, classes three, warm look, import culling, it'll Hammarby bus, ready wrangler, huge clinically, do sludge or step in data preparation or transformations. So yeah, has Yamaha mean data preparation or data exploration cup parts through the Hopis tip domain data preparation and transformation can engage me HMO counter thing to deal with missing values Othniel, whose corporeal connected courses, Catania, feet, missing rows and columns go RTD, They have yak, which mean we gotta nickel Cambridge read-only scope of Phil Carnegie courses, cut the hay or data go. A Top Transform, cupcake, rope, military attack, EMOC, huge costs like there could be null value. Yeah. Anyway I lose novel. So yeah, happy, I'm look categorizing app am look would update, have an RFP, happy my X or Y DO teacher longer. Yup. M cackling x k basis pay y value at x k corresponding y-values. So yeah, hmm, system repeat carrying on linear regression model. Go home, look trained carrying a, a modal banana. Does ketosis fit? Who named x-value Ham looked system, if it calling it will have a corresponding y value. They are great. So you're happy I'm Luke is data Cambyses pyramidal system, both will continue to happen, may crack along x. It got added but not all number yet it np dot array my huge gone well known by everyone unequally immerse. There are five pre-print, 25-35, 4545 upwards with a secure PRP, 25-50, 5K, 354515 Kurdish 25-30 J up, viscoelasticity, five-carbon DJ, screw up, 75 per cycle. Some jockey for garden is crop. 1982, Israel lookup, which we lesser kinetic. To support the Hamada XOR y, yeah. Yeah, permitted dot recept, Yahweh dot recept to NumPy, array me up column or row score defined candidates. The outcome will take gamma Hami column TA, or roads, neighborhood advocate indicator gap and minus one to one no-man's land area was called multi demonstrate anatomy, convert cut. They got Odyssey. Tell us, I'm Luke, why an API? We're not a multidimensional array and PID bananas, Hey, one-dimensional area. So you have a dihedral. Exhaled were FCRA, IQ column or multiple roads KSR data. Although IQ, Rwanda right across multiple columns add together. Though cookie has_many x co convert cars, the eye color Mona Cato, you keep all of my vacuum allergists war room earnings come here to get album cackling at the sludge tip you have warhead linear regression model made a taco fleet carrying it, right? So hmm, look by lin linear regression model. When I get some huge killing a model equal to linear regression function, cobol language, your linear regression function cold call cutting was k by them look, tackling and model.predict, model.predict category Jackie is linear regression model go FITC oligarchies pay X or Y data. Joe Humira, pilot data XOR y to Amelia, who's k bases pay yea its model coef fit courier, or just keep them cackling and linear recreation dot fit x, y. So it's fit dot XY colinear regress and moral capacity building it or ERP Amara. Do linear regression model have what the anodic XY value skip bases pay or is quote Kwame, luck, getting it to Hamada model to have Wu ready Hodeidah. I'll gladly cackling each step for each tape four mm carrying achy results find coming up to the amniotic Mod model there CALEA F0 is modeled, quote to him, Look, it's model. Cto. Hm, Look, it's modelled Muhammad camel, Decca coefficient values, manga constant coefficient, dual linear regression, K COPC and say Jacobi sin off regress on a. We have over Y equal to m x plus c, a m or C value jackhammer Mileva, hey, I'm cackling R-squared module.js score XY carrying it or has a coefficient of determination or intercept values mean Django model r squared r underscores quahog corpus in the data or intercept. Kelly, I'm Lo model dot intercept underscore cunning little yea Homais intercept key-value their data or slope, go hmmm, lung model dot coefficent cutting a model coefficient or yummy slope key value that they got. Oh yummy ham look, cackling it. Qin economic model, benign, oldest Mamluk cackling and linear regression one-syllable called cunning Alfred dot X comma Y dot VC. Abby happy, I'm look, I kind of get why cul-de-sac gotta just make column over on multiple rows on autos Kiva. You happy. Interceptors. Slope cup gave me a copy. Santos Couperin killing u2 is quote unquote ridiculous. Coming out, put camel into the opposite click, coefficient of determination it Nia into separate Nia slope it Nia on now wallah intercept, yeah. Yeah. Or slope you have it Nia lab work same evaluate UK, I'm Nick, which be changed to make Yahweh stick. Why qualm really SIP Gatto, CME where leukemia, pinwheel rehab, up, gambler cutting it. I won't look at linear regression. Models apply Kirchhoff's prediction, cutting it. So yeah, Pam can find canola, why predicts and cookie x k basis primar y co predict canal Yap Democrat cutting it. White predicts an equal to Y predicate model.predict yaks, so yaks, happy I'm predicts bunks on coding gain. Dorky Hammarby model can predict Krieger to model.predict Katherine Maxwell who colleague our predict function odd k values predicts like escape, I suspect, do hominid linear regression can model now skip kit-based pay. Or you happy I'm look at getting it predicted response, Yankee white bread or coefficient, intercept or coefficent going happy. Print, JOB Hami, intercept, myopic will there, which list step memory they got Kasim Nicholson and your coefficient was calm Luca wreck wij equal to m x plus c may fit Ck are there. So you have him look at em to him model intercept will directly OPM model dot intercept, correct? Plus model dot coefficient into eax anarchy, yogas T, model dot intercept year Mary Jo value where Yahoo AC or Yahoo get m coefficient or 3x 1202 0s value Kwame law, It's simple, straight line equation. We are regression line Kate Freed, correct. Wipe Brit Co, phonically at the white bread Cal gum modelling intercept plus modal coefficient into eax. So yummy white, equation D, They got y-value giga, headache, model, intercept key, Kelly or Yup, I'm look predicted response code from blowing up a print, cutting it. So IBM lobby score and killing to the Tamika or put multiple Yap in the KML output MLA predictor response 102421152730 or is made they can gauge or from an aqueous and we do Camara, your model predict caribou, Kalevala, OR DO hamlet ERP intercept requests and mu value fluid Kirchner, Joe, Nikola, Warby, Haumea. Same result there and no-no here result will call VCE, will police embryonic yup do model predict Korea or Joe coefficient k basis B, I'm low, manually fried turkey and the Columbia Homais CME y-values. Then you want to hand to Yamada model, the arrow guy or A-bomb. Yummy. Predicts and be the intellect album cackling, yum, update model.predict cunning and new datacenters and you're happier, thalami obstinate, but on a day-to-day basis per He predict QA, right? Hmmm cackling, it can't make NAD dataset linger or school Hamlet is modal. Middle-income. Maxwell lose our y-value. I'm look predicating the app Hamlet calculate caret dx mu dx nu gamma of nu x by loot, you haven't Mexico np dot orange ten, or reciprocal minus one, comma one and Q one column or multiple rosemary 10 to nine and a manana, n and p dot ten cachaca, 0 to 900. They got like a Tokyo digital scuffled, 100 others though. Okay. So you calculate again predator and 0 to 9100 to ten, you make anything that you do. Two key, du by dt anosmia indexing should rotate Eurocentric 0 to nine giga and get those ten elements cake. And even IGA, I'll just come locally, say minus one comma one current McCloskey, one column of our rows, get maybe data points on growth narrows been other economies could print corrects. New Nucor, dagger, d rho two Niantic and Emile Galle, right? A-bomb cackling gave predict centering model could huge Turkey. So you hop in Mecca, which control? The optima. You'd cut out, Jaap him. But that can now, why new? Now I'll skip this. It's been a while. A y-value Hammarby model called huge curcuit Guan millenia regress on Turkey. But I'll just go Hamlet train Kayak is payoff Nippur anyway, extra y, value, spare, Joham, 10X, feed key attack, Happy Valley step may, right? Yap it. Hamlet by Alice step Mays quote Joe, data feed kettles kept him a modern, we'll get a stamp query x where Laura linear term and a y values. We'll Lang Happy model. Why new kilogram model.predict xx news. So model.predict constantly Jovian Maxwellian rolling Awami, IQ was kick corresponding y value they got do we have an immoral go train key wire. So you happy Hamid. Why? New eligible jangled otolithic Tamika, new eligible test. The camp MAY well Ujamaa level camera it it 0.9499.5 to assay. I may thus x-value CALEA. So eastern US, they humble yet to have Wacom aria, Scalia, ne y-values, Abdulhamid Amara, linear decrease and more electronic Arcadia to East allocates the HUM LOG linear regression model called huge construct. The hymn predicts an canonically though linear regression AARP, I'm low linear regression modelling. But a massacre Tokyo opcode years. Some admire her work in linear regression co-op Cassie, huge cost something to subset by lamb import cutting-edge Ruby libraries, MHA classes, two-year, pyramid recreate corrects or why feed Hmm, add ACO, model modality, linear regression, classical call Turkey modellers fit my x and y culprit career progress and come model humble, not a half-filled whose model cut-through, I'm Luke, 4% copper that Korea or y-value could predict, correct? Or you have family coefficient, could alka wij called them extremists plus seemed to be a miss him, you lose millenials. Guadalajara model data with some leak. Data. Create K x nu, get o to nine I carry when I go home there is model dot predict amygdala or nay, why you Andrews will get reached that occur hmm, linearly the so-called huge costs, OK, the hair predicts and CALEA. 11. 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