Frameworks

Unify your entire machine learning workflow with all your favorite data science tools, languages, frameworks and compute. Connect any data source, algorithm, and your favorite package, and programming language.

Flexible ML Platform

Flexible

Use any language, AI framework, and compute environment. Integrate and version any kind of data to reuse in any project, experiment, and/or notebook

Interactive ML Platform

Interactive

Use any development environment like JupyterLab, RStudio, and more with pre-installed dependencies and version control

Unified ML Platform

Interactive

One unified environment to manage, build and deploy your machine learning with all your favorite data science tools

An open source library and framework used by data scientists to design, build, and train deep learning models and large-scale machine learning

An Python open source neural network library used for fast experimentation with deep neural networks

 

An open source machine learning library used for computer vision and natural language processing (NLP)

 

Also known as Scikit-learn, SKLearn is a free Python machine learning library featured various classification, regression and clustering algorithms including support for vector machines, random forests, and gradient poosting

A programming language and free software environment for statistical computing and graphics commonly used by statisticians and data miners

 

 

An intuitive and simplistic language and framework to program your machine learning models

 

 

 

 

 

A data science framework and open source software library for executing end-to-end data science on graphics processing units (GPUs)

A high-level programming language used to write any application and is well-suited for numerical analysis and computational science

An open source deep learning framework specializing in language, machine vision, and multimedia

 

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