| Course Description |
| Giving Computers the Ability to Learn from Data Building intelligent machines to transform data into knowledge. |
| A Tour of Machine Learning Classifiers Using scikit-learn. |
| Building Good Training Sets – Data Preprocessing. |
| Solving interactive problems with reinforcement learning. |
| Discovering hidden structures with unsupervised learning. |
| A roadmap for building machine learning systems. |
| Evaluating models and predicting unseen data instances. |
| Artificial neurons – a brief glimpse into the early history of machine learning |
| Implementing a perceptron learning algorithm in Python |
| An object-oriented perceptron API, Training a perceptron model on the Iris dataset |
| Adaptive linear neurons and the convergence of learning. |






















