annotated-transformers

Deep Learning for humans

??? 60+ Implementations/tutorials of deep learning papers with side-by-side notes ?; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ? reinforcement learning (ppo, dqn), capsnet, distillation, ... ?

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

Python Data Science Handbook: full text in Jupyter Notebooks

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Visualizer for neural network, deep learning and machine learning models

The fundamental package for scientific computing with Python.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

? A ranked list of awesome machine learning Python libraries. Updated weekly.

A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support