this post was submitted on 09 Nov 2023
20 points (81.2% liked)
Programming
17343 readers
440 users here now
Welcome to the main community in programming.dev! Feel free to post anything relating to programming here!
Cross posting is strongly encouraged in the instance. If you feel your post or another person's post makes sense in another community cross post into it.
Hope you enjoy the instance!
Rules
Rules
- Follow the programming.dev instance rules
- Keep content related to programming in some way
- If you're posting long videos try to add in some form of tldr for those who don't want to watch videos
Wormhole
Follow the wormhole through a path of communities !webdev@programming.dev
founded 1 year ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
So I should learn sklearn first before pytorch to understand the basics?
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.
If you get the hang of "classical" ML, then deep learning becomes easy as it's still machine learning, just with more complicated models and no closed-form solutions.
Aight thanks.