I had an assigned task to make the requested changes and refactor the scratch linear regression model. The tests and documentation are complete and are ready to merge along with the model. I will now be working mostly on scikit models from now.
1. Linear Regression
2. k Nearest neighbours
Challenges are mostly in making the code more understandable and neat. I have been following a protocol of implementing the algorithm in an external repo and then after discussing with mentor, wrapping it as neatly as possible.
Another challenge is debugging, there is no set way to check/debug the code so I have to simultaneously write tests and make sure they are meaningful. This is one of the reasons why scratch Linear Regression took so much time.
Resource I am using:
I really wanted to mention this and would probably write a separate blog on this but for now I am majorly following scikit documentation and an amazing python channel named 'sentdex' on youtube.