Ask HN: Materials to learn machine learning and deep learning in 2023?
The materials may include courses, tutorials, books, etc.
The topics can include:
1. Data pre-processing
2. Library specific tutorials (e.g. PyTorch, MxNet, scikit-learn, etc)
3. Building things from scratch (using numpy, scipy, vanilla python, etc)
4. Foundations and theory behind the popular algorithms
5. Applications like Computer Vision, NLP, etc.
6. How to read and implement research papers.
7. The math of ML/DL
The difficulty of the materials can be anything ranging from someone with programming experience starting out or someone who is a practitioner and wants to look at more deeper explanations. CMU has two open courses on deep learning which are very good. 1. Deep Learning - https://deeplearning.cs.cmu.edu/F23/index.html 2. Deep Learning Systems - https://dlsyscourse.org/ The second course dives much deeper into the internals of the libraries and all.