User:Fkdosilovic/Books/Introduction to Machine Learning
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Introduction to Machine Learning
[edit]- 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