Machine Learning
by Achilles Rasquinha

1. Types of Learning
1.1. Supervised Learning
1.1.1. Classification
1.1.1.1. based-on types
1.1.1.1.1. Binary Classification
1.1.1.1.2. Multi-Class Classification
1.1.1.2. based-on algorithms
1.1.1.2.1. Logistic Regression
1.1.1.2.2. k-Nearest Neighbours
1.1.2. Regression
1.1.2.1. Linear Regression
1.2. Semi-Supervised Learning
1.3. Unsupervised Learning
1.3.1. Clustering
1.3.1.1. K-Means
1.4. Reinforcement Learning
2. How to approach a Problem?
2.1. Define your Problem
2.1.1. Problem Statement
2.1.2. Problem Description
2.1.3. Data Set Description
3. Deep Learning
3.1. Architectures
3.1.1. Convolutional Neural Networks
3.1.2. Recurrent Neural Networks
3.1.2.1. GRU