google-research/tuning_playbook

A hyperparameter optimization framework

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

VIP cheatsheets for Stanford's CS 230 Deep Learning

Machine Learning Engineering Open Book

Go ahead and axolotl questions

🧑‍🏫 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, ... 🧠

The fastai book, published as Jupyter Notebooks

An educational resource to help anyone learn deep reinforcement learning.