Completed
- Test random actions with dummy agent
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Hyperparameter Optimization for Reinforcement Learning Using Meta's Ax
Automatically move to the next video in the Classroom when playback concludes
- 1 - Introduction
- 2 - What are hyperparameters
- 3 - Hyperparameter optimization loop
- 4 - Grid search
- 5 - Random search
- 6 - Bayesian optimization
- 7 - Install Python packages
- 8 - Import Python packages
- 9 - Configure Weights & Biases
- 10 - Set deterministic mode
- 11 - Load pendulum gymnasium environment
- 12 - Test pendulum environment
- 13 - Test random actions with dummy agent
- 14 - Testing and logging callbacks
- 15 - Define trial to train and test an agent
- 16 - Define project settings and hyperparameter ranges
- 17 - Create gymnasium environment
- 18 - Define Ax experiment to perform Bayesian optimization for hyperparameters
- 19 - Perform hyperparameter optimization and debugging
- 20 - Train agent with best hyperparameters
- 21 - Test agent
- 22 - Run additional trials
- 23 - Weights & Biases sweeps
