Linear Regression with Gradient Descent From Scratch with Numpy

Timestamps
0:00 - 0:26 Introduction
0:27 - 4:32 Visualizing The Salary Data
4:33 - 7:37 Measuring Error with MSE
7:38 - 11:34 Gradient Descent In Depth Explanation
11:35 - 18:15 Algorithm Implementation
18:16 - 21:20 Linear Regression Visualization
21:20 - 21:57 Outro
Try my FAVORITE coding rescource:
www.datacamp.com?tap_a=5644-dce66f&tap_s=1065405-0291e3&
If you have any questions or if you want me to attach the code lmk down below!!
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[@John-xi2im]

amazingly explained tutorial! The concept was explained with the most simplistic but complete explanation possible! thanks a lot !

[@ruwindananayakkara1942]

Great work man, It would be great to see what you are typing, when you are typing it. Kind of frustrating to wait for a scroll

[@TheTeenInnovator]

Noted!

[@ronyakar8321]

Super informative! Keep it up

[@TheTeenInnovator]

Melech 🤘

[@munocat]

Very informative, thank you

[@TheTeenInnovator]

Thank you so much!!

[@xdarshan]

how would we do it for multiple x values?

[@TheTeenInnovator]

Could you specify your question more, like do you want to do multivariate regression?

[@xdarshan]

@@TheTeenInnovator yeah!

[@TheTeenInnovator]

Yeah so that's a great question! You essentially just need to add n columns to the X data your analysing and then your equation becomes a little different, and as dimensionality increases so does complexity (it's fascinating!) I would start here bit.ly/3lGNvJo, and Andrew Ng's Course Explains it beautifully

[@xdarshan]

@@TheTeenInnovator ahm, i still do not understand. it would be great if you could make a follow up video :) i get it conceptually, but can't put it to code

[@TheTeenInnovator]

Alright I gotchu, I will make a tutorial in the next few days I think many other people benefit from it, it seems like its a pretty confusing topic to understand