User:Fkdosilovic/Books/Introduction to Machine Learning

Introduction to Machine Learning

 * Introduction
 * Machine learning
 * Supervised learning
 * Unsupervised learning


 * Regression
 * Outline of regression analysis
 * Regression analysis
 * Dependent and independent variables
 * Linear model
 * Linear regression
 * Least squares
 * Linear least squares (mathematics)
 * Feature (machine learning)
 * Feature vector


 * Search Methods
 * Nearest neighbor search
 * K-nearest neighbors algorithm
 * Stochastic gradient descent
 * Beam search
 * Best-first search
 * Breadth-first search
 * Hill climbing
 * Hyperparameter optimization
 * Brute-force search
 * Depth-first search
 * Tabu search
 * Anytime algorithm


 * Support Vector Machines
 * Kernel method
 * Support vector machine
 * Structural risk minimization
 * Empirical risk minimization
 * Least squares support vector machine
 * Relevance vector machine
 * Sequential minimal optimization
 * Structured support vector machine


 * Clustering
 * Cluster analysis
 * K-means clustering
 * K-means++
 * K-medians clustering


 * Neural Networks
 * Artificial neural network
 * Artificial neuron
 * Types of artificial neural networks
 * Perceptron
 * Multilayer perceptron
 * Activation function
 * Deep learning