45 - Linear regression using Sci-Kit Learn in Python

This is a follow up to the previous video where I explained the theory behind Linear Regression. In this video, I go through the process of using Sci-kit learn in Python to perform Linear Regression on data imported from a csv file.
The code from this video is available at: github.com/bnsreenu/python_fo...

[@casimirronnlof7396]

Thank you! I tried to find a very beginner-friendly tutorial, and this is the best one I've found!

[@DigitalSreeni]

Great to hear!

[@studyroomMB]

Great video. I've had classes for both machine learning and deep learning. I've passed the classes with good grades,but this series has really helped me deepen my understanding over data analysis in general. Great job on your videos,I'm very thankful!

[@abhaikumar10]

One of the best expatiations. 👏👏👏👏👏👏👏👏

[@sidohamadi4635]

Thank you sreeni

[@javi19841000]

Very good video, Thank you so much... Good work

[@ishakaumaru6704]

this is marvelous..... i am searching through your channel right now to explore more... i am a beginner in machine learning and i believe your tutoring approach is giving big hope

[@DigitalSreeni]

Welcome aboard!

[@surflaweb]

this is not very good is AMAZING. thanks sir I learned a lot with this tutorials. Thanks for share the code also.. keep it up

[@felip6180]

The R² value is good, and the residual plot (using seaborn) shows the randomness of the residue, implying the fit was good

[@et1428]

You are the best.

[@theminertom11551]

Great content!

[@1UniverseGames]

Thank you sir, learned a lot as a novice student

[@DigitalSreeni]

Glad to hear that

[@himanshu8006]

thanks, it was helpful

[@DigitalSreeni]

Glad to hear that!

[@nazilakheiryuni]

thanks

[@sathishkumarpalani9511]

Very nice lecture sir

[@DigitalSreeni]

Thanks for liking

[@GeorgeC1andonly]

in case anyone gets "module not found" for sklearn - open conda prompt and run "conda install -c anaconda scikit-learn"

[@lizakalaijian883]

thanks alot for the Video. Where can we find the file you were using?

[@finnmccool8671]

Good tutorial. Simple and straight forward. Maybe a plot of the regression line and the original data points would have been nice for a visual. Seaborn does this but I don't think it gives the equation for the line??

[@DigitalSreeni]

You are right, Seaborn displays the linear regression line by default but it does not display the equation. Of course you can always get the slope and intercept values using linregress from stats in scipy package (or linear_model in sklearn like I showed in the video).

[@ojicletus5066]

Hi Sreeni, why didn't you train_test_split in testing and training the model? Is it ok to train the model directly without splitting the data set. please explain to me when it is necessary to used train_test_split

[@DigitalSreeni]

I do not do train and test split for linear regression as the fitting provides MSE metric that reflects the accuracy of the fit.

[@et1428]

Why do you predict 2.3?

[@hasanshaikh2014]

this lecture is not up to the level as compared to other lectures @sreeni please explain with more examples when you write the code because at some point in time it feels like what is the use of this code and why it is written.

[@DigitalSreeni]

It is unfortunate that you do not find the explanation to be clear. Any suggestions on what is missing so I can fix it the next time I cover this topic?

[@hasanshaikh2014]

@@DigitalSreeni after watching the 6th time this lecture now I understand the whole concept which is covered in this lecture.