The Wolfram Language includes a wide range of state-of-the-art integrated machine learning capabilities, from highly automated functions like Predict and Classify to functions based on specific methods and diagnostics, including the latest neural net approaches. The functions work on many types of data, including numerical, categorical, time series, textual, image and audio.
Classify — classify data into categories using a built-in classifier or learning from examples
Predict — predict values from data using a built-in predictor or learning from examples
ClassifierFunction — symbolic representation of a classifier to be applied to data
PredictorFunction — symbolic representation of a predictor to be applied to data
SequencePredict — predict subsequent elements from sequence examples
SequencePredictorFunction — symbolic representation of a sequence predictor
DimensionReduction — find how to project data onto lower-dimensional space
FeatureExtraction — find how to extract features from data
ClusterClassify — classify data into clusters
FindDistribution — find a simple symbolic distribution from data
FeatureSpacePlot — visualization of dimension-reduced feature space
Dendrogram — visualization of hierarchical clusters
BayesianMinimization — model-based minimization of arbitrary objective functions
ActiveClassification — learn a classifier by actively probing a system
ActivePrediction — learn a predictor by actively probing a system
NetGraph — represent an arbitrary neural network structure
NetTrain — train any neural network on CPUs, GPUs, etc.
NetModel — collection of trained and untrained models
FeatureExtractor — how to extract features to learn from
FeatureTypes — feature types to assume for input data
PerformanceGoal — whether to optimize for memory, quality, or speed
TimeGoal — how long to allocate for training, etc.
RandomSeeding — how to seed randomization
DeleteMissing — delete missing elements in data
Standardize — transform data to have zero mean and unit variance
MovingAverage — compute moving averages of lists, time series, etc.
ImageIdentify — recognize objects in images
ImageRestyle — restyle an image according to samples