1. Introduction and Configuration
2. The three different types of machine learning
3. Supervised Machine Learning Classification and Regression
4. Unsupervised Machine Learning Reinforcement Learning
5. Introduction to the basic terminology, notations and roadmap
6. Training Simple Machine Learning Algorithms for Classification
7. Implementing a perception learning algorithm in Python
8. Implementing a perceptron learning algorithm in Python
9. Training a perceptron model on the Iris dataset
10. Perceptron Training Prediction
11. Perceptron Decision Boundaries
12. Adaptive linear neurons and the convergence of learning
13. Adaptive linear neurons and the convergence of learning
14.zip
