MACHINE LEARNING

1. CLUSTERING

1.1. K-Means

1.2. k-Medians

1.3. Expectation maximization

1.4. Hierarchical

1.5. Self-organizing maps

2. DEEP LEARNING

2.1. Multi-layer perceptron

2.2. Recurrent neural networks

2.3. Convolutional neural networks

2.4. Boltzmann machine

2.5. Multi-layer autoencoder

3. CLASSIFICATION

3.1. K-NEAREST NEIGHBOUR

3.2. Support Vector Machine

3.3. Naive Bayes

3.4. Decision tree

4. REGRESSION

4.1. Linear Rgression

4.2. Multivariate linear regression

4.3. Logistic regression

4.4. Cox regression