Regression Mathematics
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- เผยแพร่เมื่อ 6 ก.ย. 2024
- Everyone needs to understand regression! Its a useful data science technique that allows us to understand the relationship between different variables. In this video, we'll play the role of a newly hired data analyst at a genetics company trying to find the relationship between advertising mediums (TV, newspaper, radio) and ticket sales to our newly opened theme park. Along the way, we'll learn about 5 types of regression models (linear, non-linear, multiple, lasso, and ridge). Expect math, code, and layers of explanation. Enjoy!
Code for this video:
github.com/llS...
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"Microsoft run by TH-cam sensation Bill Gates" lmfao dead
7:50 How exactly is the graph in the middle an example of a linear regression model when the actual graph is not a linear function? curvature as mentioned later is the exact opposite of something that has a linear progression. ..or am I missing something important here?
I also have the same question.
Regression is a powerful tool for forecasting. Economists using it successfully predicted ten out of the last two recessions ...
Does that mean they are not factoring in all the variables (of which there might be trillions as anything can affect the economy worldwide)?
@@catalepsy8916 The number of variables that are needed to be processed for a perfect prediction are beyond our computation power as of now ..
Indeed
@@lugrisa R, STATA, MATLAB, GRETL, eViews, there are a lot of software solutions for econometrics nowadays, that it's actually hard to choose "correct one". IMHO Learning Python seems most reasonable for me nowadays, thanks to sheer amount of libraries
Notification : Hey, Siraj just uploa....
Me: Say no more...
From India?
@@ParmodKumar-fw7jy yep
Love the interpretation of the regularization term as introducing bias to reduce variance! All the other people so far explained it as a penalty for having high weights, which is intuitive and nice to understand but do not include this second aspect of a bias term. Thank you for this insight, Siraj!
This is my entire base for starting Data Science :D
At 3:14 you say that the dependent variable can also be called the predictor variable. I believe it's called the response variable instead. Predictor/explanatory/independent variables are the same.
great intro Siraj! Agree with Bookerer... predictors are the independent variables X
Yes, Predictors are independent variables(x1,x2,....xn). But, dependent variable is Predicted (Y)
I've seen some machine learning courses that used the term "predictor" for the dependent variable.
I prefer to use Random Forest, Support Vector Regression and Decision Tree Regression to solving my regression problem sometimes Polynomial Regression is also giving a good prediction on a test set.
In EDA, if we find the collinearity between two features, whether dropping one of those features or combing them to a single feature and using normal regression techniques helps? Or, is it necessary that we should go for LASSO or RIDGE regression?
Much respect to Siraj. Always well knowledge and versed on the subject matter
Best video on regression!
Just explained how to do my senior assignment better than my teacher.
Random Forrest is it powerful model to regression problem? @Siraj_Rawal
Is there a closed form solution of ridge regression with the non-negativity constraint of output variable?
Siraj hits gym I guess so🤓🤓
I need to know to predict dataset like csv to make machine learning.... With sklearn I didn't succeed to make It when I import and load my dataset with dataframe like df=pd.read_csv("")..
I need little help... thank you so much for your request..
I need to use sklearn to make machine learning.
Why lasso penalise the high coefficient to zero while ridge only makes it a reduced value?
For anyone interested, I wrote a few of detailed python notebooks on linear regression and also ridge + lasso a while ago:
Linear Regression Notebook + PDF note (applied to Fifa 2018 data):
github.com/hammadshaikhha/Math-of-Machine-Learning-Course-by-Siraj/tree/master/Linear%20Regression
Ridge Regression (applied to IMDB data):
github.com/hammadshaikhha/Math-of-Machine-Learning-Course-by-Siraj/blob/master/Regularization%20in%20Linear%20Regression/Regularization%20in%20Linear%20Regression.ipynb
Lasso and Ridge Regression for model selection (applied to NY school data):
github.com/hammadshaikhha/Math-of-Machine-Learning-Course-by-Siraj/blob/master/Linear%20Model%20Selection/Linear%20Model%20Selection.ipynb
I don’t know if you saw my other comment, but you are talking much slower now and your videos are way better!
Hey siraj, Can you create a video which tells how to actually create a dataset from received signals? There is not much documentation given for dataset using signal processing. Thanks.
You are great sir, inspiring and improving skillset the fun way.
Hi siraj, thanks for uploading this video, I have a question, in the end of the video, you said, if the y has high collinearity with independent, its better to use lasso or ridge regression, but how can I ensure I have high collinearity? Should I ensure hight collinearity through r2 ( r square) please advise me
Hey man, just wanted to let you know that I really appreciate your videos.
Nice explain
Can i Know Math behind the linear regression
At 3:11 he means Y_i = \beta_0 + \beta_1 X_i instead of Y_i = \beta_0 + \beta_1 X_1 , where i index your couple (X,Y) of your dataset.
I'm working on a dataset for a predictive analytics project around 5 GB. Preprocessing them takes up all the time. Is there a way to parallelise and speed up the process?
How can we work if we have to apply a linear regression in a complex-valued dataset?
Do you have a vid buidling on one of your two regression vids for multi-variable regression?
I love this guy
I love lizard girl
Who wants to be a MLionaire
seasoned redditer spotted
@@VahidSaffarian what does that even mean? 🤔
The regression line at 5:24 does not follow the data at all! Although they would be so nice and linear...
Great video, Siraj. Would you be sometime doing a video tutorial on Plotly?
Always eager to see your videos 💖💖
Thanks Siraj!
When's your Meme Review with Elon?
Haha, ask him on Twitter! I’d love to this week
BST 210 squad up!!!
I wonder, how can people even give dislike on this video! Dumb people :/ They don't know how to appreciate good work.
I just made my expression of understanding
Simple Explanation to Regression
'Siraj's Quality Content'
--- Linear Regression
regression my fav
GJ man! Can I get a heat?
I love how we are relearning high school math :)
Fantastico
The question is did you use regression on pop culture references to write the script ?
Great Intro :D
How lasso make irrelevant features to zero? I mean what is the mathematics behind it?
There are another types of regression model that you didn't consider inside your list, for example: non linear, semi parametric, generalized linear models, additives models an so on
Hey Siraj! First to comment!
nice
Great video, please update the school of AI link!
1st comment and 1st like
7:00 "Does this equation explain the meaning of life?" 😁 Another great video. It's good to have these high level overviews of a topic (eg. linear regression) because they give a good framework to build on once you start studying them in depth.
I was first to view the video :)
Is Siraj's voice unusually deep here?
May be it is AI powered voice ..😀😁
the best weapon in financial trading to destroy the market makers ;)
When a tokai learns to print hello world!!
1st like
Hi Siraj,
Thank you for this video.
i want your reply on this. I am studying ML for a long time but unable to crack the interview. i try to follow your 3 months ML curriculum. but unable to understand what to do, where to work. where to do practices i dont know.
please help me on this. Thanks!
when u r studying for long time, then why r you so confused.
Make 1-2 portfolio projects.... like for self-driving car, swarm intelligence etc.
@@DeependraTube I dont know how to start, plz share some reference links.
@@AshishTyagi2911 Do u know Coding already ?
If so , you can go to fast.ai and search youtube for Andrew Ng course , and also Coursera have good courses.
Yo
Any video with Math on it's title gets auto-downvoted instantly by a script I'm running on background. Crap!
It’s funny how the video is entirely about linear regression and I didn’t hear the word “correlation coefficient” one time.
First
those hands 😂
Early
Second
404 ERROR: RAP SONG NOT FOUND
Really... Fortnite..
waste of time
I was there for your session in Mumbai. You were so amazing