Comment on [question] Which ML library should I learn in Python?
AlmightySnoo@lemmy.world 10 months ago
I’d say since you’re a beginner, it’s much better to try to implement your regression functions and any necessary helper functions (train/test split etc…) yourself in the beginning. Learn the necessary linear algebra and quadratic programming and try to implement linear regression, logistic regression and SVMs using only numpy and cvxpy.
Once you get the hang of it, you can jump straight into sklearn and be confident that you understand sort of what those “blackboxes” really do and that will also help you with troubleshooting.
Asudox@lemmy.world 10 months ago
So I should learn sklearn first before pytorch to understand the basics?
AlmightySnoo@lemmy.world 10 months ago
Linear and logistic regression are much easier (and less error prone) to implement from scratch than neural network training with backpropagation.
That way you can still follow the progression I suggested: implement those regressions by hand using numpy -> compare against (and appreciate) sklearn -> implement SVMs by hand using cvxpy -> appreciate sklearn again.
Asudox@lemmy.world 10 months ago
Aight thanks.