In 2023 which is the best path to get good at machine and deep learning?

Question

Which is the best resource (book, public course, blogs, etc) to get started in machine and deep learning and then get good at it both as a practitioner and from theoretical understanding?The ultimate goal is to become a good at implementing models and come up with new ones.Is there something like teachyourselfCS but for Data Science, ML and DL?

ggr2342 · Accepted Answer

Start with fast.ai courses for learning Deep Learning at the practitioner level.

GoldenMonkey · Answer

Caltech machine learning intro course: https://www.youtube.com/watch?v=mbyG85GZ0PI
karpathy's Zero to Hero series (https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThs...)
meta llama 2 - is open source https://github.com/facebookresearch/llama/tree/main
Tools:
ai - hosting Banana - Machine Learning Model Deployment on Serverless GPUs https://www.banana.dev
pinecone - vector database: https://www.pinecone.io
how to run AI language models on a single cpu pc - https://news.ycombinator.com/item?id=34869960

brudgers · Answer

[delayed]

tikkun · Answer

I collected some resources on this. See: https://news.ycombinator.com/item?id=36195527

YossarianFrPrez · Answer

Once you've learned what you can from online resources and textbooks, doing projects -- from Kaggle, etc. -- is a good way to practice applying what you've learned.

max_ · Answer

For the basics read Micheal's Neural Nets & Deep learning - http://neuralnetworksanddeeplearning.com/
The Watch the Caltech telecourse - https://work.caltech.edu/telecourse
Read tutorials on Pytorch, Tensorflow & Keras.
Read, source codes on hugging face and deploys, test, train toy models.
Test your skills by participating in Data scientist competitions like Kaggle or Numerai.
It will give you a great way of guaging your competence with other data scientists.