Machine Learning Tools
The best Machine Learning Tools based on votes, our collection of reviews, verified products
and a total of 132 factors
Latest update:
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TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
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Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.
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Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
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scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
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Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.
freemium
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Comet lets you track code, experiments, and results on ML projects. Itβs fast, simple, and free for open source projects.
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Deep Learning and AI accessible to everyone
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Open source deep learning platform that provides a seamless path from research prototyping to...
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Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
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Datatron automates the deployment, monitoring, governance, and validation of your machine learning models in scikit-learn, TensorFlow, Keras, Pytorch, R, H20 and SAS
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MLKit is a simple machine learning framework written in Swift.
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Machine Learning Operationalization
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Developer tools for deep learning research