Machine Learning Tutorial Python - 17: L1 and L2 Regularization | Lasso, Ridge Regression

In this Python machine learning tutorial for beginners, we will look into,
1) What is overfitting, underfitting
2) How to address overfitting using L1 and L2 regularization
3) Write code in Python and sklearn for housing price prediction where we will see a model overfit when we use simple linear regression. Then we will use Lasso regression (L1 regularization) and ridge regression (L2 regression) to address this overfitting issue

#MachineLearning #PythonMachineLearning #MachineLearningTutorial #Python #PythonTutorial #PythonTraining #MachineLearningCource #L1andL2Regularization #Regularization #sklearntutorials #scikitlearntutorials

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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

[bharathis]

Statquest theory+Codebasics Practical implementation=😍😍😍

[AlonAvramson]

I have been following all 17 videos on ML you provided so far and found this is the best resource to learn from . Thank you!

[gyanaranjanbal]

Clean, crisp and crystal clear, I was struggling to understand this from a long time, your 20 mins video cleared it in one attempt, thanks a lot💌💌

[DrizzyJ]

Bro, you don't know how you've helped me in my computer vision journey. Thank you❤❤❤

[bhavikjain]

A good video to understand the practical implementation of L1 and L2. Thank You

[javiermarchenahurtado]

Such a great video!! I was struggling to understand regularization and now it's crystal clear to me!

[tusharsethi]

One of the best videos out there for Regularization.

[piyushlanjewar]

That's a really great explanation, Anyone can use this method in real use cases now. Keep it up.

[haintuvn]

Thank you for your interesting video. As far as I get from the video, L1, L2 regulations help to overcome the overfit problem from Linear regression! What is about other algorithms ( Support vector machine, logistic regression..), how can we overcome the overfit problem?

[amruth]

Sir your all the vedios are really helpful...Now Iam giving you the feed back of the vedio Iam going to see.This is also an beautiful vedio and Hyperparamter tuning also an very best Bless you..u..work hard in getting think to understand in easy manner..

[ajaykushwaha-jemw]

Best tutorial on l1 and L2 Regularization.

[joehansie]

All your videos are totally great. Keep working on it

[phuonglethithanh]

Thank you for this video. Very straightforward and comprehensive ❤

[Hari-xrob]

you should probably change the X and Y axes. Matches won is a function of Age. So, Age should be on X axis and Matches won on Y axis

[atulupadhyay]

machine learning concepts and practicals made easy, Thank you so much Sir <3

[shashankdhananjaya]

Couldn't have explained it any simpler. Perfect tutorial.

[nastaran]

best learning with very good explanation. Thanks

[nationhlohlomi]

I really love your content….. You change lives❤❤❤

[yashvd]

As per the equation y = mX + c, you inter-changed the y & X axis, if I'm not wrong.
Because you are trying to predict match won(yhat) which is your horizontal line and age(X) is on vertical line.
Maybe using something unconventional mislead new-learners.
As X is a horizontal line and y is vertical line, that's what we learned since school time.
Assigning X & y to axis(as per your explanation) will be great help to learner.
I hope you are not taking personally. My opologies if so!

[kouider]

Just came across this video accidentally simply great thank you