This repo contains the instructions for the ML for Good bootcamp, for students and researchers interested in AI safety.
The program is aimed at beginners in machine learning, but is quite ambitious, and we hope that even advanced students will enjoy participating in this program.
We draw inspiration from the redwood mlab, and ARENA, both of which focuses mainly on the ML engineering part. However there are a lot more workshops on strategy, goverance and conceptual AI safety during the ML4G.
- agents: agents normal, agents, agents hard
- fsgm patch attack: fsgm patch attack
- gradcam: gradcam
- hyperparameters: hyperparameters
- induction heads: induction heads normal, induction heads hard, induction heads
- optimisation: optimisation
- optimizers: optimizers normal, optimizers
- pytorch tuto: pytorch tuto
- rl: DQN workbook empty hard, A2C workbook complete, DQN workbook empty, A2C workbook empty, A2C workbook empty hard, DQN workbook complete
- rlhf: rlhf
- tensors: tensors
- transformer: transformer
- transformer interp: transformer interp
- vanilla policy gradient: vanilla policy gradient
Before contributing to the project, you need to read the guidelines and follow the instructions in CONTRIBUTING.md.