Machine Learning Frameworks

Machine learning frameworks are essential tools for developing and deploying machine learning models. They provide a wide range of functionalities and are designed to simplify the process of building and training models.

Top Machine Learning Frameworks

Here is a list of some popular machine learning frameworks:

• TensorFlow: An open-source machine learning framework developed by Google Brain team.
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• PyTorch: An open-source machine learning library based on the Torch library, developed by Facebook's AI Research lab.
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• Keras: A high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.
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• Scikit-learn: A Python-based library for machine learning that provides simple and efficient tools for data analysis and modeling.
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• Apache MXNet: A flexible and efficient machine learning framework for both beginners and experts.
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• Microsoft Cognitive Toolkit (CNTK): An open-source, commercial-grade toolkit for deep learning.
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Further Reading

For more information on machine learning frameworks, you can visit our Machine Learning Resources page.