Outline of machine learning
The following outline is provided as an overview of and topical guide to machine learning. Machine learning is a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from an example training set of input observations in order to make datadriven predictions or decisions expressed as outputs, rather than following strictly static program instructions.
What ''type'' of thing is machine learning?
 An academic discipline
 A branch of science
 * An applied science
 ** A subfield of computer science
 *** A branch of artificial intelligence
 *** A subfield of soft computing
 ** Application of statistics
Branches of machine learning
Subfields of machine learning
Subfields of machine learning Computational learning theory  studying the design and analysis of machine learning algorithms.
 Grammar induction
 Meta learning
Crossdisciplinary fields involving machine learning
 Adversarial machine learning
 Predictive analytics
 Quantum machine learning
 Robot learning
 * Developmental robotics
Applications of machine learning
 Bioinformatics
 Biomedical informatics
 Computer vision
 Customer relationship management 
 Data mining
 Email filtering
 Inverted pendulum  balance and equilibrium system.
 Natural language processing
 * Automatic summarization
 * Automatic taxonomy construction
 * Dialog system
 * Grammar checker
 * Language recognition
 ** Handwriting recognition
 ** Optical character recognition
 ** Speech recognition
 * Machine translation
 * Question answering
 * Speech synthesis
 * Text mining
 **Term frequency–inverse document frequency
 * Text simplification
 Pattern recognition
 * Facial recognition system
 * Handwriting recognition
 * Image recognition
 * Optical character recognition
 * Speech recognition
 Recommendation system
 *Collaborative filtering
 *Contentbased filtering
 *Hybrid recommender systems
 Search engine
 *Search engine optimization
 Social Engineering
Machine learning hardware
 Graphics processing unit
 Tensor processing unit
 Vision processing unit
Machine learning tools
 Comparison of deep learning software
 * Comparison of deep learning software/Resources
Machine learning frameworks
Proprietary machine learning frameworks
Proprietary machine learning frameworks Amazon Machine Learning
 Microsoft Azure Machine Learning Studio
 DistBelief  replaced by TensorFlow
Open source machine learning frameworks
 Apache Singa
 Apache MXNet
 Caffe
 PyTorch
 mlpack
 TensorFlow
 Torch
 CNTK
 Accord.Net
Machine learning libraries
 Deeplearning4j
 Theano
 Scikitlearn
 Keras
Machine learning algorithms
Types of machine learning algorithms
 Almeida–Pineda recurrent backpropagation
 ALOPEX
 Backpropagation
 Bootstrap aggregating
 CN2 algorithm
 Constructing skill trees
 Dehaene–Changeux model
 Diffusion map
 Dominancebased rough set approach
 Dynamic time warping
 Errordriven learning
 Evolutionary multimodal optimization
 Expectation–maximization algorithm
 FastICA
 Forward–backward algorithm
 GeneRec
 Genetic Algorithm for Rule Set Production
 Growing selforganizing map
 Hyper basis function network
 IDistance
 Knearest neighbors algorithm
 Kernel methods for vector output
 Kernel principal component analysis
 Leabra
 Linde–Buzo–Gray algorithm
 Local outlier factor
 Logic learning machine
 LogitBoost
 Manifold alignment
 Markov chain Monte Carlo
 Minimum redundancy feature selection
 Mixture of experts
 Multiple kernel learning
 Nonnegative matrix factorization
 Online machine learning
 Outofbag error
 Prefrontal cortex basal ganglia working memory
 PVLV
 Qlearning
 Quadratic unconstrained binary optimization
 Querylevel feature
 Quickprop
 Radial basis function network
 Randomized weighted majority algorithm
 Reinforcement learning
 Repeated incremental pruning to produce error reduction
 Rprop
 Rulebased machine learning
 Skill chaining
 Sparse PCA
 State–action–reward–state–action
 Stochastic gradient descent
 Structured kNN
 Tdistributed stochastic neighbor embedding
 Temporal difference learning
 Wakesleep algorithm
 Weighted majority algorithm
Machine learning methods
 Instancebased algorithm
 * Knearest neighbors algorithm
 * Learning vector quantization
 * Selforganizing map
 Regression analysis
 * Logistic regression
 * Ordinary least squares regression
 * Linear regression
 * Stepwise regression
 * Multivariate adaptive regression splines
 Regularization algorithm
 * Ridge regression
 * Least Absolute Shrinkage and Selection Operator
 * Elastic net
 * Leastangle regression
 Classifiers
 * Probabilistic classifier
 ** Naive Bayes classifier
 * Binary classifier
 * Linear classifier
 * Hierarchical classifier
Dimensionality reduction
 Canonical correlation analysis
 Factor analysis
 Feature extraction
 Feature selection
 Independent component analysis
 Linear discriminant analysis
 Multidimensional scaling
 Nonnegative matrix factorization
 Partial least squares regression
 Principal component analysis
 Principal component regression
 Projection pursuit
 Sammon mapping
 tdistributed stochastic neighbor embedding
Ensemble learning
 AdaBoost
 Boosting
 Bootstrap aggregating
 Ensemble averaging  process of creating multiple models and combining them to produce a desired output, as opposed to creating just one model. Frequently an ensemble of models performs better than any individual model, because the various errors of the models "average out."
 Gradient boosted decision tree
 Gradient boosting machine
 Random Forest
 Stacked Generalization
Meta learning
 Inductive bias
 Metadata
Reinforcement learning
 Qlearning
 State–action–reward–state–action
 Temporal difference learning
 Learning Automata
Supervised learning
 AODE
 Artificial neural network
 Association rule learning algorithms
 * Apriori algorithm
 * Eclat algorithm
 Casebased reasoning
 Gaussian process regression
 Gene expression programming
 Group method of data handling
 Inductive logic programming
 Instancebased learning
 Lazy learning
 Learning Automata
 Learning Vector Quantization
 Logistic Model Tree
 Minimum message length
 * Nearest Neighbor Algorithm
 * Analogical modeling
 Probably approximately correct learning learning
 Ripple down rules, a knowledge acquisition methodology
 Symbolic machine learning algorithms
 Support vector machines
 Random Forests
 Ensembles of classifiers
 * Bootstrap aggregating
 * Boosting
 Ordinal classification
 Information fuzzy networks
 Conditional Random Field
 ANOVA
 Quadratic classifiers
 knearest neighbor
 Boosting
 * SPRINT
 Bayesian networks
 * Naive Bayes
 Hidden Markov models
 *Hierarchical hidden Markov model
Bayesian
 Bayesian knowledge base
 Naive Bayes
 Gaussian Naive Bayes
 Multinomial Naive Bayes
 Averaged OneDependence Estimators
 Bayesian Belief Network
 Bayesian Network
Decision tree algorithms
 Decision tree
 Classification and regression tree
 Iterative Dichotomiser 3
 C4.5 algorithm
 C5.0 algorithm
 Chisquared Automatic Interaction Detection
 Decision stump
 Conditional decision tree
 ID3 algorithm
 Random forest
 SLIQ
Linear classifier
 Fisher's linear discriminant
 Linear regression
 Logistic regression
 Multinomial logistic regression
 Naive Bayes classifier
 Perceptron
 Support vector machine
Unsupervised learning
 Expectationmaximization algorithm
 Vector Quantization
 Generative topographic map
 Information bottleneck method
Artificial neural networks
 Feedforward neural network
 * Extreme learning machine
 * Convolutional neural network
 Recurrent neural network
 * Long shortterm memory
 Logic learning machine
 Selforganizing map
Association rule learning
 Apriori algorithm
 Eclat algorithm
 FPgrowth algorithm
Hierarchical clustering
 Singlelinkage clustering
 Conceptual clustering
Cluster analysis
 BIRCH
 DBSCAN
 Expectationmaximization
 Fuzzy clustering
 Hierarchical Clustering
 Kmeans clustering
 Kmedians
 Meanshift
 OPTICS algorithm
Anomaly detection
 knearest neighbors classification
 Local outlier factor
Semisupervised learning
 Active learning  special case of semisupervised learning in which a learning algorithm is able to interactively query the user to obtain the desired outputs at new data points.
 Generative models
 Lowdensity separation
 Graphbased methods
 Cotraining
 Transduction
Deep learning
 Deep belief networks
 Deep Boltzmann machines
 Deep Convolutional neural networks
 Deep Recurrent neural networks
 Hierarchical temporal memory
 Generative Adversarial Networks
 Deep Boltzmann Machine
 Stacked AutoEncoders
Other machine learning methods and problems
 Anomaly detection
 Association rules
 Biasvariance dilemma
 Classification
 * Multilabel classification
 Clustering
 Data Preprocessing
 Empirical risk minimization
 Feature engineering
 Feature learning
 Learning to rank
 Occam learning
 Online machine learning
 PAC learning
 Regression
 Reinforcement Learning
 Semisupervised learning
 Statistical learning
 Structured prediction
 * Graphical models
 ** Bayesian network
 ** Conditional random field
 ** Hidden Markov model
 Unsupervised learning
 VC theory
Machine learning research
 List of artificial intelligence projects
 List of datasets for machine learning research
History of machine learning
 Timeline of machine learning
Machine learning projects
 DeepMind
 Google Brain
Machine learning organizations
 Knowledge Engineering and Machine Learning Group
Machine learning conferences and workshops
 Artificial Intelligence and Security
 Conference on Neural Information Processing Systems
 ECML PKDD
 International Conference on Machine Learning

Machine learning publications
Books on machine learning
Books about machine learningMachine learning journals
 Machine Learning
 Journal of Machine Learning Research
 Neural Computation
Persons influential in machine learning
 Alberto Broggi
 Andrei Knyazev
 Andrew McCallum
 Andrew Ng
 Anuraag Jain
 Armin B. Cremers
 Ayanna Howard
 Barney Pell
 Ben Goertzel
 Ben Taskar
 Bernhard Schölkopf
 Brian D. Ripley
 Christopher G. Atkeson
 Corinna Cortes
 Demis Hassabis
 Douglas Lenat
 Eric Xing
 Ernst Dickmanns
 Geoffrey Hinton  coinventor of the backpropagation and contrastive divergence training algorithms
 HansPeter Kriegel
 Hartmut Neven
 Heikki Mannila
 Ian Goodfellow  Father of Generative & adversarial networks
 Jacek M. Zurada
 Jaime Carbonell
 Jeremy Slovak
 Jerome H. Friedman
 John D. Lafferty
 John Platt  invented SMO and Platt scaling
 Julie Beth Lovins
 Jürgen Schmidhuber
 Karl Steinbuch
 Katia Sycara
 Leo Breiman  invented bagging and random forests
 Lise Getoor
 Luca Maria Gambardella
 Léon Bottou
 Marcus Hutter
 Mehryar Mohri
 Michael Collins
 Michael I. Jordan
 Michael L. Littman
 Nando de Freitas
 Ofer Dekel
 Oren Etzioni
 Pedro Domingos
 Peter Flach
 Pierre Baldi
 Pushmeet Kohli
 Ray Kurzweil
 Rayid Ghani
 Ross Quinlan
 Salvatore J. Stolfo
 Sebastian Thrun
 Selmer Bringsjord
 Sepp Hochreiter
 Shane Legg
 Stephen Muggleton
 Steve Omohundro
 Tom M. Mitchell
 Trevor Hastie
 Vasant Honavar
 Vladimir Vapnik  coinventor of the SVM and VC theory
 Yann LeCun  invented convolutional neural networks
 Yasuo Matsuyama
 Yoshua Bengio
 Zoubin Ghahramani
Other
 Anne O'Tate
 Ant colony optimization algorithms
 Anthony Levandowski
 Antiunification
 Apache Flume
 Apache Giraph
 Apache Mahout
 Apache SINGA
 Apache Spark
 Apache SystemML
 Aphelion
 Arabic Speech Corpus
 Archetypal analysis
 Arthur Zimek
 Artificial ants
 Artificial bee colony algorithm
 Artificial development
 Artificial immune system
 Astrostatistics
 Averaged onedependence estimators
 Bagofwords model
 Balanced clustering
 Ball tree
 Base rate
 Bat algorithm
 Baum–Welch algorithm
 Bayesian hierarchical modeling
 Bayesian interpretation of kernel regularization
 Bayesian optimization
 Bayesian structural time series
 Bees algorithm
 Behavioral clustering
 Bernoulli scheme
 Bias–variance tradeoff
 Biclustering
 BigML
 Binary classification
 Bing Predicts
 Bioinspired computing
 Biogeographybased optimization
 Biplot
 Bondy's theorem
 Bongard problem
 Bradley–Terry model
 BrownBoost
 Brown clustering
 Burst error
 CBCL
 CIML community portal
 CMAES
 CURE data clustering algorithm
 Cache language model
 Calibration
 Canonical correspondence analysis
 Canopy clustering algorithm
 Cascading classifiers
 Category utility
 CellCognition
 Cellular evolutionary algorithm
 Chisquare automatic interaction detection
 Chromosome
 Classifier chains
 Cleverbot
 Clonal selection algorithm
 Clusterweighted modeling
 Clustering highdimensional data
 Clustering illusion
 CoBoosting
 Cobweb
 Cognitive computer
 Cognitive robotics
 Collostructional analysis
 Commonmethod variance
 Completelinkage clustering
 Computerautomated design
 Concept class
 Concept drift
 Conference on Artificial General Intelligence
 Conference on Knowledge Discovery and Data Mining
 Confirmatory factor analysis
 Confusion matrix
 Congruence coefficient
 Connect
 Consensus clustering
 Constrained clustering
 Constrained conditional model
 Constructive cooperative coevolution
 Correlation clustering
 Correspondence analysis
 Cortica
 Coupled pattern learner
 Crossentropy method
 Crossvalidation
 Crossover
 Cuckoo search
 Cultural algorithm
 Cultural consensus theory
 Curse of dimensionality
 DADiSP
 DARPA LAGR Program
 Darkforest
 Dartmouth workshop
 DarwinTunes
 Data Mining Extensions
 Data exploration
 Data preprocessing
 Data stream clustering
 Dataiku
 Davies–Bouldin index
 Decision boundary
 Decision list
 Decision tree model
 Deductive classifier
 DeepArt
 DeepDream
 Deep Web Technologies
 Defining length
 Dendrogram
 Dependability state model
 Detailed balance
 Determining the number of clusters in a data set
 Detrended correspondence analysis
 Developmental robotics
 Diffbot
 Differential evolution
 Discrete phasetype distribution
 Discriminative model
 Dissociated press
 Distributed R
 Dlib
 Document classification
 Documenting Hate
 Domain adaptation
 Doubly stochastic model
 Dualphase evolution
 Dunn index
 Dynamic Bayesian network
 Dynamic Markov compression
 Dynamic topic model
 Dynamic unobserved effects model
 EDLUT
 ELKI
 Edge recombination operator
 Effective fitness
 Elastic map
 Elastic matching
 Elbow method
 Emergent
 Encog
 Entropy rate
 Erkki Oja
 Eurisko
 European Conference on Artificial Intelligence
 Evaluation of binary classifiers
 Evolution strategy
 Evolution window
 Evolutionary Algorithm for Landmark Detection
 Evolutionary algorithm
 Evolutionary art
 Evolutionary music
 Evolutionary programming
 Evolvability
 Evolved antenna
 Evolver
 Evolving classification function
 Expectation propagation
 Exploratory factor analysis
 F1 score
 FLAME clustering
 Factor analysis of mixed data
 Factor graph
 Factor regression model
 Factored language model
 Farthestfirst traversal
 Fastandfrugal trees
 Feature Selection Toolbox
 Feature hashing
 Feature scaling
 Feature vector
 Firefly algorithm
 Firstdifference estimator
 Firstorder inductive learner
 Fish School Search
 Fisher kernel
 Fitness approximation
 Fitness function
 Fitness proportionate selection
 Fluentd
 Folding@home
 Formal concept analysis
 Forward algorithm
 Fowlkes–Mallows index
 Frederick Jelinek
 Frrole
 Functional principal component analysis
 GATTO
 GLIMMER
 Gary Bryce Fogel
 Gaussian adaptation
 Gaussian process
 Gaussian process emulator
 Gene prediction
 General Architecture for Text Engineering
 Generalization error
 Generalized canonical correlation
 Generalized filtering
 Generalized iterative scaling
 Generalized multidimensional scaling
 Generative adversarial network
 Generative model
 Genetic algorithm
 Genetic algorithm scheduling
 Genetic algorithms in economics
 Genetic fuzzy systems
 Genetic memory
 Genetic operator
 Genetic programming
 Genetic representation
 Geographical cluster
 Gesture Description Language
 Geworkbench
 Glossary of artificial intelligence
 Glottochronology
 Golem
 Google matrix
 Grafting
 Gramian matrix
 Grammatical evolution
 Granular computing
 GraphLab
 Graph kernel
 Gremlin
 Growth function
 HUMANT algorithm
 Hammersley–Clifford theorem
 Harmony search
 Hebbian theory
 Hidden Markov random field
 Hidden semiMarkov model
 Hierarchical hidden Markov model
 Higherorder factor analysis
 Highway network
 Hinge loss
 Holland's schema theorem
 Hopkins statistic
 Hoshen–Kopelman algorithm
 Huber loss
 IRCF360
 Ian Goodfellow
 Ilastik
 Ilya Sutskever
 Immunocomputing
 Imperialist competitive algorithm
 Inauthentic text
 Incremental decision tree
 Induction of regular languages
 Inductive bias
 Inductive probability
 Inductive programming
 Influence diagram
 Information Harvesting
 Information fuzzy networks
 Information gain in decision trees
 Information gain ratio
 Inheritance
 Instance selection
 Intel RealSense
 Interacting particle system
 Interactive machine translation
 International Joint Conference on Artificial Intelligence
 International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics
 International Semantic Web Conference
 Iris flower data set
 Island algorithm
 Isotropic position
 Item response theory
 Iterative Viterbi decoding
 JOONE
 Jabberwacky
 Jaccard index
 Jackknife variance estimates for random forest
 Java Grammatical Evolution
 Joseph Nechvatal
 Jubatus
 Julia
 Junction tree algorithm
 KSVD
 Kmeans++
 Kmedians clustering
 Kmedoids
 KNIME
 KXEN Inc.
 K qflats
 Kaggle
 Kalman filter
 Katz's backoff model
 Kernel adaptive filter
 Kernel density estimation
 Kernel eigenvoice
 Kernel embedding of distributions
 Kernel method
 Kernel perceptron
 Kernel random forest
 Kinect
 KlausRobert Müller
 Kneser–Ney smoothing
 Knowledge Vault
 Knowledge integration
 LIBSVM
 LPBoost
 Labeled data
 LanguageWare
 Language Acquisition Device
 Language identification in the limit
 Language model
 Large margin nearest neighbor
 Latent Dirichlet allocation
 Latent class model
 Latent semantic analysis
 Latent variable
 Latent variable model
 Lattice Miner
 Layered hidden Markov model
 Learnable function class
 Least squares support vector machine
 Leaveoneout error
 Leslie P. Kaelbling
 Linear genetic programming
 Linear predictor function
 Linear separability
 Lingyun Gu
 Linkurious
 Lior Ron
 List of genetic algorithm applications
 List of metaphorbased metaheuristics
 List of text mining software
 Local casecontrol sampling
 Local independence
 Local tangent space alignment
 Localitysensitive hashing
 Loglinear model
 Logistic model tree
 Lowrank approximation
 Lowrank matrix approximations
 MATLAB
 MIMIC
 MXNet
 Mallet
 Manifold regularization
 Margininfused relaxed algorithm
 Margin classifier
 Mark V. Shaney
 Massive Online Analysis
 Matrix regularization
 Matthews correlation coefficient
 Mean shift
 Mean squared error
 Mean squared prediction error
 Measurement invariance
 Medoid
 MeeMix
 Melomics
 Memetic algorithm
 Metaoptimization
 Mexican International Conference on Artificial Intelligence
 Michael Kearns
 MinHash
 Mixture model
 Mlpy
 Models of DNA evolution
 Moral graph
 Mountain car problem
 Movidius
 Multiarmed bandit
 Multilabel classification
 Multi expression programming
 Multiclass classification
 Multidimensional analysis
 Multifactor dimensionality reduction
 Multilinear principal component analysis
 Multiple correspondence analysis
 Multiple discriminant analysis
 Multiple factor analysis
 Multiple sequence alignment
 Multiplicative weight update method
 Multispectral pattern recognition
 Mutation
 MysteryVibe
 Ngram
 NOMINATE
 Nativelanguage identification
 Natural Language Toolkit
 Natural evolution strategy
 Nearestneighbor chain algorithm
 Nearest centroid classifier
 Nearest neighbor search
 Neighbor joining
 Nest Labs
 NetMiner
 NetOwl
 Neural Designer
 Neural Engineering Object
 Neural Lab
 Neural modeling fields
 Neural network software
 NeuroSolutions
 Neuro Laboratory
 Neuroevolution
 Neuroph
 Niki.ai
 Noisy channel model
 Noisy text analytics
 Nonlinear dimensionality reduction
 Novelty detection
 Nuisance variable
 Numenta
 Oneclass classification
 Onnx
 OpenNLP
 Optimal discriminant analysis
 Oracle Data Mining
 Orange
 Ordination
 Overfitting
 PROGOL
 PSIPRED
 Pachinko allocation
 PageRank
 Parallel metaheuristic
 Parity benchmark
 Partofspeech tagging
 Particle swarm optimization
 Path dependence
 Pattern language
 Peltarion Synapse
 Perplexity
 Persian Speech Corpus
 Picas
 Pietro Perona
 Pipeline Pilot
 Piranha
 Pitman–Yor process
 Plate notation
 Polynomial kernel
 Pop music automation
 Population process
 Portable Format for Analytics
 Predictive Model Markup Language
 Predictive state representation
 Preference regression
 Premature convergence
 Principal geodesic analysis
 Prior knowledge for pattern recognition
 Prisma
 Probabilistic Action Cores
 Probabilistic contextfree grammar
 Probabilistic latent semantic analysis
 Probabilistic soft logic
 Probability matching
 Probit model
 Product of experts
 Programming with Big Data in R
 Proper generalized decomposition
 Pruning
 Pushpak Bhattacharyya
 Q methodology
 Qloo
 Quality control and genetic algorithms
 Quantum Artificial Intelligence Lab
 Queueing theory
 Quick, Draw!
 R
 Rada Mihalcea
 Rademacher complexity
 Radial basis function kernel
 Rand index
 Random indexing
 Random projection
 Random subspace method
 Ranking SVM
 RapidMiner
 Rattle GUI
 Raymond Cattell
 Reasoning system
 Regularization perspectives on support vector machines
 Relational data mining
 Relationship square
 Relevance vector machine
 Relief
 Renjin
 Repertory grid
 Representer theorem
 Rewardbased selection
 Richard Zemel
 Right to explanation
 RoboEarth
 Robust principal component analysis
 RuleML Symposium
 Rule induction
 Rules extraction system family
 SAS
 SNNS
 SPSS Modeler
 SUBCLU
 Sample complexity
 Sample exclusion dimension
 Santa Fe Trail problem
 Savi Technology
 Schema
 Searchbased software engineering
 Selection
 SelfService Semantic Suite
 Semantic folding
 Semantic mapping
 Semidefinite embedding
 Sense Networks
 Sensorium Project
 Sequence labeling
 Sequential minimal optimization
 Shattered set
 Shogun
 Silhouette
 SimHash
 SimRank
 Similarity measure
 Simple matching coefficient
 Simultaneous localization and mapping
 Sinkov statistic
 Sliced inverse regression
 Snakes and Ladders
 Soft independent modelling of class analogies
 Soft output Viterbi algorithm
 Solomonoff's theory of inductive inference
 SolveIT Software
 Spectral clustering
 Spikeandslab variable selection
 Statistical machine translation
 Statistical parsing
 Statistical semantics
 Stefano Soatto
 Stephen Wolfram
 Stochastic block model
 Stochastic cellular automaton
 Stochastic diffusion search
 Stochastic grammar
 Stochastic matrix
 Stochastic universal sampling
 Stress majorization
 String kernel
 Structural equation modeling
 Structural risk minimization
 Structured sparsity regularization
 Structured support vector machine
 Subclass reachability
 Sufficient dimension reduction
 Sukhotin's algorithm
 Sum of absolute differences
 Sum of absolute transformed differences
 Swarm intelligence
 Switching Kalman filter
 Symbolic regression
 Synchronous contextfree grammar
 Syntactic pattern recognition
 TDGammon
 TIMIT
 Teaching dimension
 Teuvo Kohonen
 Textual casebased reasoning
 Theory of conjoint measurement
 Thomas G. Dietterich
 Thurstonian model
 Topic model
 Tournament selection
 Training, test, and validation sets
 Transiogram
 Trax Image Recognition
 Trigram tagger
 Truncation selection
 Tucker decomposition
 UIMA
 UPGMA
 Ugly duckling theorem
 Uncertain data
 Uniform convergence in probability
 Unique negative dimension
 Universal portfolio algorithm
 User behavior analytics
 VC dimension
 VIGRA
 Validation set
 Vapnik–Chervonenkis theory
 Variableorder Bayesian network
 Variable kernel density estimation
 Variable rules analysis
 Variational message passing
 Varimax rotation
 Vector quantization
 Vicarious
 Viterbi algorithm
 Vowpal Wabbit
 WACA clustering algorithm
 WPGMA
 Ward's method
 Weasel program
 Whitening transformation
 Winnow
 Win–stay, lose–switch
 Witness set
 Wolfram Language
 Wolfram Mathematica
 Writer invariant
 Xgboost
 Yooreeka
 Zeroth