We provide here a suite of Python examples that walk you through concepts in:
-
Classical & Deep Reinforcement Learning
-
Basic & Advanced Machine Learning
Usage of the examples is simple: just run the main file for each project. Each project example contains its own README.md
file discussing the theory and applications.
![](/daniel-xion/LearningX/raw/master/classical_RL/multiarmed_bandit/images/coverart.png)
![](/daniel-xion/LearningX/raw/master/classical_RL/gridworld/images/coverart.png)
![](/daniel-xion/LearningX/raw/master/classical_RL/blackjack/images/coverart.png)
![](/daniel-xion/LearningX/raw/master/deep_RL/cartpole/images/cartpole.gif)
![](/daniel-xion/LearningX/raw/master/deep_RL/pong/images/pong.gif)
![](/daniel-xion/LearningX/raw/master/basic_ML/classification/images/coverart.png)
- Decision Tree, K-Nearest Neighbours, Logistic Regression (Gradient Descent)
![](/daniel-xion/LearningX/raw/master/basic_ML/regression/images/coverart.png)
- Linear Regression (Gradient Descent / Stochastic Gradient Descent)
![](/daniel-xion/LearningX/raw/master/basic_ML/unsupervised/images/coverart.png)
- K-means Clustering
![](/daniel-xion/LearningX/raw/master/advanced_ML/model_tree/images/coverart.png)
![](/daniel-xion/LearningX/raw/master/advanced_ML/tree_ensembles/images/coverart_bagging.png)
![](/daniel-xion/LearningX/raw/master/advanced_ML/tree_ensembles/images/coverart_boosting.png)
Anson Wong