TensorFlow Alternatives & Competitors

Open source deep learning platform that provides a seamless path from research prototyping to...

Key PyTorch features:

Dynamic Computation Graph Pythonic Nature Strong Community Support Flexibility and Control

Open Source

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Key Keras features:

User-Friendly Modularity Pre-trained Models Integration with TensorFlow

Open Source

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Key KeywordSearch features:

AI Ad Targeting AI Keyword Research AI Audience Builder YouTube Ad Spy

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scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Key Scikit-learn features:

Ease of Use Extensive Documentation and Community Support Integration with Other Libraries Variety of Algorithms

Open Source

Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

Key IBM Watson Studio features:

Integration Scalability Collaboration Automated Machine Learning (AutoML)

Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.

Key H2O.ai features:

Open Source AutoML Scalability Wide Range of Algorithms

Open Source

Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.

Key Azure Machine Learning Studio features:

User-Friendly Interface Integration with Azure Services Pre-built Algorithms Collaborative Environment

Build and deploy machine learning models in a simplified way with Azure Machine Learning service. Make machine learning more accessible with automated capabilities.

Key Azure Machine Learning Service features:

Integrated Environment Scalability Automated Machine Learning Security and Compliance

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Key CUDA Toolkit features:

Performance Support for Parallel Programming Rich Development Ecosystem Comprehensive Libraries

Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

Key Amazon SageMaker features:

Fully Managed Service Scalability Integrated Development Environment Support for Popular Machine Learning Frameworks

The best-in-class, rapid no-code Pega Platform is unified for building BPM, CRM, case management, and real-time decisioning apps.

Key Pega Platform features:

Low-Code Development Scalability Case Management AI and Decisioning

RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

Key RapidMiner features:

Ease of Use Integration Capabilities Comprehensive Feature Set Community and Support

Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.

Key Google Cloud Machine Learning features:

Integrated Environment Scalability Automated Machine Learning (AutoML) Integration with Google Services

Open Source

MLKit is a simple machine learning framework written in Swift.

Key MLKit features:

Feature-Rich Ease of Integration Regular Updates Open-Source

Open Source