Machine Learning

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