SUMMARY.md

Table of contents

• README
  • Title Page
  • Introduction
  • Half Title
  • Authors
  • Dedication
  • Acknowledgements
  • Preface
  • Copyright

Chapters

• Actor-critic
• AdaBoost
• Adadelta
• Adagrad
• Adam
• Affinity Propagation
• Apriori
• Asynchronous Advantage Actor-Critic
• Averaged One-Dependence Estimators
• Back-Propagation
• Bayesian Network
• Boosting
• Bootstrapped Aggregation
• C5.0
• CatBoost
• Chi-squared Automatic Interaction Detection
• Classification and Regression Tree
• Conditional Decision Trees
• Convolutional Neural Network
• Decision Stump
• Deep Belief Networks
• Deep Boltzmann Machine
• Deep Q-Network
• Density-Based Spatial Clustering of Applications with Noise
• Differential Evolution
• Eclat
• Elastic Net
• Expectation Maximization
• eXtreme Gradient Boosting
• Flexible Discriminant Analysis
• Gated Recurrent Unit
• Gaussian Naive Bayes
• Genetic
• Gradient Boosted Regression Trees
• Gradient Boosting Machines
• Gradient Descent
• Hidden Markov Models
• Hierarchical Clustering
• Hopfield Network
• Independent Component Analysis
• Isolation Forest
• Iterative Dichotomiser 3
• k-Means
• k-Medians
• k-Nearest Neighbor
• Label Propagation Algorithm
• Label Spreading
• Latent Dirichlet Allocation
• Learning Vector Quantization
• Least Absolute Shrinkage and Selection Operator
• Least-Angle Regression
• LightGBM
• Linear Discriminant Analysis
• Linear Regression
• Locally Estimated Scatterplot Smoothing
• Locally Weighted Learning
• Logistic Regression
• Long Short-Term Memory Network
• M5
• Mini-Batch Gradient Descent
• Mixture Discriminant Analysis
• Momentum
• Monte Carlo Tree Search
• Multidimensional Scaling
• Multilayer Perceptrons
• Multinomial Naive Bayes
• Multivariate Adaptive Regression Splines
• Nadam
• Naive Bayes
• Ordinary Least Squares Regression
• Partial Least Squares Regression
• Particle Swarm Optimization
• Perceptron
• Policy Gradients
• Principal Component Analysis
• Principal Component Regression
• Projection Pursuit
• Proximal Policy Optimization
• Q-learning
• Quadratic Discriminant Analysis
• Radial Basis Function Network
• Random Forest
• Recurrent Neural Network
• Reinforcement Learning
• Ridge Regression
• RMSProp
• Rotation Forest
• Sammon Mapping
• Self-Organizing Map
• Semi-Supervised Support Vector Machines
• Simulated Annealing
• Spectral Clustering
• Stacked Auto-Encoders
• Stacked Generalization
• State-Action-Reward-State-Action
• Stepwise Regression
• Stochastic Gradient Descent
• Support Vector Machines
• Support Vector Regression
• t-Distributed Stochastic Neighbor Embedding
• TD-Lambda
• Weighted Average