The repository contains notebooks with implementation of different AI concepts
Other great educational material:
- DeepMinds Educational Resources
- The most full read list of AI resources
- The most full watch list of AI resources
- ML Course Notes
- Deep Learning in Hebrew - book by Avraham Ravid
- Understanding Deep Learning, by Simon J.D. Prince
- Understanding Deep Learning, by Simon J.D. Prince, MIT press
- Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI, by Shlomo Kashani, Amir Ivry
- Excellent ML course by Argmax company
- Deep Learning Resource in Hebrew
Papers and books:
- Geometric foundations of Deep Learning
- Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges
- Reinforcement Learning, by Sutton and Barto
Visualizations:
- Visualize gradient descent optimization algorithms in Tensorflow
- Scientific Visualization: Python + Matplotlib
Geometric Deep Learning
- Geometric Deep Learning course, by Michael Bronstein (Oxford/Twitter) • Joan Bruna (NYU) • Taco Cohen (Qualcomm) • Petar Veličković (DeepMind)
- Stanford CS224W: Machine Learning with Graphs
NLP
Datasets