Linear Regression with Python | Sklearn Machine Learning Tutorial

In this hands-on python tutorial, we will learn the fundamentals of machine learning and linear regression in the context of a problem, and generalize their definitions.

🎯 Topics Covered
• Preparing data for machine learning
• Linear regression with multiple features
• Generating predictions and evaluating models

scikit-learn/17900

⌚ Time Stamps:
00:00 Course Overview
07:15 Introduction
09:31 Problem Statement
21:25 Downloading and exploring a dataset for machine learning
58:10 Linear regression using a single feature
1:27:31 Linear regression using scikit-learn
1:46:09 Linear Regression with multiple variables
1:55:31 Using categorical features machine learning
2:11:27 Model Improvements
2:29:10 Summary and Conclusion

⚡ Free Certification Course

🎤 About the speaker
Aakash N S is the co-founder and CEO of Jovian - a community learning platform for data science & ML. Previously, Aakash has worked as a software engineer (APIs & Data Platforms) at Twitter in Ireland & San Francisco and graduated from the Indian Institute of Technology, Bombay. He’s also an avid blogger, open-source contributor, and online educator.

#GBM #sklearntutorial #LinearRegression #Certification #Course #Jovian

-

[ayushranjanroy]

It is unbelievable that this course is free.

[sandeepgupta]

Request you to please consider a course on NLP : basic to advanced. That will be really helpful

[vishaljhaveri]

I wish this course is as good as Data Analysis with Python.
Love you, team Jovian.
Aakash N G, you are the best tutor.
I am too excited to start this course.
Lots of love from Surat!

Thank you so much for this!!!!

[colabpro]

I hope you know that you're incredibly good at teaching, Aakash. 🥺🥺🙏 Moreover, your concepts are crystal clear. You've helped me in understanding the concepts quite a lot. I've gotta immense respect for you.

Sending blessings and good vibes your way. Stay blessed 🙂🙏

[Kevin-exvr]

i have to tell you, this is, combined with the andrew ng intuition videos, the best class on linear regression out there. Congratulations.

[priyanksanghvi]

Fantastic course!!!!
Even after watching several videos and classes, I still couldn't grasp ML concepts.
However, only this first lecture clarified a lot of topics.

Thank you very much for creating this series.

[davida]

Perhaps one of the best ML beginner course I've seen in a while. Even better than the ones that arent free!

[nishant_poddar]

Thank you for the hard work behind in making all your courses free.

[gurjeet]

Feeling excited to be part of this course.

[abdullahmuhammadmoosa]

You are an unbelievable tutor <3 you explain everything so simply! Thank you so much for giving this course for free!

[Griffindor]

Great Video!
I cannot believe you don't charge for this quality learning. Keep it up!

[arunkumar-jpte]

Awesome content sir. I was searching for these concepts in YouTube from last one week. Finally my searching stopped here. The way you are teaching and content is fabulous.

[bihanbanerjee]

Thanks for making this whole course free. I was exactly looking for a course like this... thanks a lot.. <3 ... It's really unimaginable this content is for free...

[oladejiakomolafe]

Very clear explanation, from the depth of my heart, I say thank you.

[arjuqureshi]

Happy to learn from u, such a wonderful explaination

[tuffOG]

Wow! Awesomely interpreted content! Keep it up, guys!

[thecardtrickstudent]

1:34:25 "hmm, Hi!" I as well as tons of other people would love nothing but to say "hi" to you and thank you as well for the wonderful opportunity you have provided through JOvian

[zuxfcnd]

Hi, thank you so much for your course. It is really useful, I enjoy this so much. The fact that it is free makes it brilliant. But one thing I would like to correct in this video. At 1:51:41, it should be w3*children but not w3*charges. Target cant be a feature. Thank you!

[vinayaktigadi]

very unique and nice way of teaching!! Thank you

[sachinsoni]

Please make a complete course on Python AI A to Z. Please make it practical like these tutorials. Every ML tutorial out there is complicated because of theoretical explanation.