User:Jqveenstra/Books/ml


 * Committee machine
 * Machine learning
 * Accuracy paradox
 * Action model learning
 * Active learning (machine learning)
 * Adaptive projected subgradient method
 * Adversarial machine learning
 * AIXI
 * Algorithmic inference
 * Apprenticeship learning
 * Bag-of-words model
 * Ball tree
 * Base rate
 * Bayesian interpretation of regularization
 * Bayesian optimization
 * Bias–variance tradeoff
 * Binary classification
 * Bongard problem
 * Bradley–Terry model
 * Catastrophic interference
 * Category utility
 * CBCL (MIT)
 * CIML community portal
 * Computational learning theory
 * Concept drift
 * Concept learning
 * Conditional random field
 * Confusion matrix
 * Constrained conditional model
 * Coupled pattern learner
 * Cross-entropy method
 * Cross-validation (statistics)
 * Curse of dimensionality
 * Data pre-processing
 * Decision list
 * Deep learning
 * Deeplearning4j
 * Developmental robotics
 * Dimensionality reduction
 * Discriminative model
 * Document classification
 * Domain adaptation
 * Eager learning
 * Early stopping
 * Elastic matching
 * Empirical risk minimization
 * Ensembles of classifiers
 * Evaluation of binary classifiers
 * Evolvability (computer science)
 * Expectation propagation
 * Explanation-based learning
 * Feature (machine learning)
 * Feature engineering
 * Feature hashing
 * Feature learning
 * Feature scaling
 * Feature vector
 * Formal concept analysis
 * Generative model
 * Google DeepMind
 * Grammar induction
 * Granular computing
 * Hyperparameter optimization
 * Inductive bias
 * Inductive functional programming
 * Inductive probability
 * Inductive programming
 * Inductive transfer
 * Inferential theory of learning
 * Instance-based learning
 * Instantaneously trained neural networks
 * Journal of Machine Learning Research
 * Kernel density estimation
 * Kernel embedding of distributions
 * Kernel random forest
 * Knowledge integration
 * Knowledge Vault
 * Large margin nearest neighbor
 * Lazy learning
 * Learning automata
 * Learning to rank
 * Learning with errors
 * Leave-one-out error
 * Linear predictor function
 * Linear separability
 * Local case-control sampling
 * M-Theory (learning framework)
 * Logic learning machine
 * Machine Learning (journal)
 * Matthews correlation coefficient
 * Meta learning (computer science)
 * Mixture model
 * Mountain Car
 * Multi-armed bandit
 * Multi-task learning
 * Multilinear principal component analysis
 * Multilinear subspace learning
 * Multiple-instance learning
 * Multivariate adaptive regression splines
 * Native-language identification
 * Nearest neighbor search
 * Neural modeling fields
 * Occam learning
 * Offline learning
 * OpenNN
 * Overfitting
 * Parity learning
 * Pattern language (formal languages)
 * Pattern recognition
 * Predictive learning
 * Predictive state representation
 * Preference learning
 * Prior knowledge for pattern recognition
 * Proactive learning
 * Probability matching
 * Product of experts
 * Proximal gradient methods for learning
 * Quantum machine learning
 * Query level feature
 * Rademacher complexity
 * Random indexing
 * Random projection
 * Representer theorem
 * Robot learning
 * Rule induction
 * Sample complexity
 * Semantic analysis (machine learning)
 * Semi-supervised learning
 * Sequence labeling
 * Similarity learning
 * Solomonoff's theory of inductive inference
 * Stability (learning theory)
 * Statistical classification
 * Statistical learning theory
 * Statistical relational learning
 * Structural risk minimization
 * Subclass reachability
 * Supervised learning
 * Test set
 * Transduction (machine learning)
 * Ugly duckling theorem
 * Uncertain data
 * Uniform convergence (combinatorics)
 * Universal portfolio algorithm
 * Unsupervised learning
 * User behavior analytics
 * Vanishing gradient problem
 * Version space learning
 * Zeroth (software)