Wolfram Computation Meets Knowledge

The Wolfram Approach to Machine Learning

Wolfram has pioneered highly automated machine learning—and deeply integrated it into the Wolfram Language—making state-of-the-art machine learning in a full range of applications accessible even to non-experts.

Use Wolfram Machine Learning to...

Automate human-judgment tasks

(medical diagnosis, quality control, emotion analysis, not safe for work, ...)

Make decisions from large-scale data

(sales forecasting, finding crime hotspots, consumer patterns, ...)

Recognize or identify objects or categories

(text, faces, brands, languages, ...)

Automate estimation tasks

(geolocation, gender, age, ...)

Predict from historical data

(projections, recommendations, logistics, ...)

Detect anomalies in data

(computer security, fraud detection, system monitoring, ...)


Automatically fill in extra or missing data

(database completion, colorization, depth reconstruction, ...)

Automatically tag elements in a large dataset

(spam filtering, sentiment analysis, image classification, ...)

Build systems that automatically adapt

(market conditions, consumer trends, continuous learning, ...)

Identify clusters and trends in data

(market segmentation, consumer trends, automatic visualization, ...)

Create customized realistic imitations

(speech synthesis, voice transfer, face transfer, computer graphics, ...)

Automate creative tasks

(handwriting synthesis, painting synthesis, music synthesis, painting from drawing, ...)


Develop new-generation efficient approximations

(math function approximations, speeding up fluid dynamics, ...)

Create embedded intelligent systems

(sensor loops, vision systems, ARM/Raspberry Pi, ...)

Update classic algorithm domains using machine learning

(signal processing, image processing, computational chemistry, control theory)

Standardize free-form or noisy data

(autocorrection, audio denoising, image deblurring, outlier removal, ...)

Teach about machine learning

(industry, higher education, K–12)

Research new machine-learning methods and analyses

(visualization, domain-specific methods, neural network architectures, ...)

and much more...

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How It Works in the Wolfram Language

Key Features of Wolfram Machine Learning

Top performance

Wolfram Machine Learning uses the latest methods and libraries, with full support for GPUs and emerging hardware and software standards

Full spectrum of methods

State-of-the-art support for classic machine-learning methods (logistic regression, SVM, random forests, ...), as well as the latest neural net and deep-learning advances

Always state-of-the-art

With its aggressive development process and constantly updated Neural Net Repository, Wolfram gives you rapid access to the latest advances in machine learning—all integrated with its automated system

Desktop, cloud, embedded, ...

Wolfram Machine Learning is immediately and seamlessly available across desktop, cloud, embedded and other platforms—leveraging Wolfram's long-term hybrid deployment strategy


Absolutely any kind of data

The Wolfram Machine Learning system has built-in support for numerical data, images, text, sounds—and arbitrary data represented through the Wolfram Language's symbolic structure

Complete automation

Wolfram has pioneered complete automation of the machine-learning process, from data preparation to method and hyperparameter selection—allowing non-experts to take full advantage of advanced machine learning

Total flexibility for experts

The Wolfram Machine Learning system provides an elegantly designed framework for complete access to all elements of the machine-learning pipeline

Integrated into your workflow

Through its deep integration into the Wolfram Language, Wolfram Machine Learning immediately fits into your existing workflows, allowing you to easily add machine learning anywhere

Develop & document in Wolfram Notebooks

Use award-winning Wolfram Notebooks to develop, document, store and share your machine-learning projects

Leverage prebuilt models and feature extractors

Dramatically reduce training times using Wolfram's expanding library of models and feature extractors

Data wrangling is built in

The Wolfram Language's unprecedentedly powerful data handling capabilities are completely integrated with the Wolfram Machine Learning system—so you don't need separate pre or post-processing

Instant APIs

All Wolfram Machine Learning can immediately be deployed as web APIs, in the public Wolfram Cloud or in Wolfram Enterprise Private Clouds


Export to standalone networks

All Wolfram neural nets can be exported to run standalone in separate programs or on separate hardware

Instant access to training data

Use Wolfram's vast knowledgebase—as well as the Wolfram Data Repository—for instant access to large-scale datasets for training

Share through Wolfram repositories

Publicly or privately share your machine-learning models through the Wolfram Cloud framework and the Wolfram Neural Net Repository

Breakthrough symbolic neural nets

Wolfram Machine Learning includes Wolfram's breakthrough symbolic framework for neural nets, providing uniquely modular and manipulable capabilities for future neural net advances

Why Speak the Wolfram Language...

Underlying everything we do is the Wolfram Language. Designed for the new generation of programmers, the Wolfram Language has a vast depth of built-in algorithms and knowledge, all automatically accessible through its elegant unified symbolic language.

  • Built-in Computable Knowledge
  • World's Largest Algorithmbase
  • Document-Based Workflow
  • High-Level Automation
  • Instant Computable Knowledge
  • Multiparadigm Language
  • Integrated All-in-One Platform
  • Symbolic-Numeric Methodology
  • Broad Subject Coverage
  • Universality of Platform
  • Natural Language Integration
  • Interactive Interfaces

Scalable for programs from tiny to huge, with immediate deployment locally and in the cloud, the Wolfram Language builds on clear principles—and 30+ years of development—to create what promises to be the world's most productive programming language.