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Homebrew GUI is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
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Homepage is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Homer is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
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hostsVN is a code project with source, releases, documentation, or setup notes.
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Hot is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Houdoku is a storage, design, or frontend resource for mockups, assets, UI tools, or web search.
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How to Secure a Linux Server is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Howdy is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Howtoscreenshot is a code repository or project page with source code, releases, documentation, or setup notes.
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Framework for distributed hyperparameter optimization.
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Making large AI models cheaper, faster and more accessible.
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Library for hyperparameter optimization and black box optimization benchmarks.
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General Machine Learning library using Numenta’s Cortical Learning Algorithm.
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Httpdownloader is a GitHub repository or organization with source code, releases, documentation, or project resources.
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Httrack is an open source project with code, documentation, and setup resources for web archiving and scraping.
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Hueblocks is a GitHub repository or organization with source code, releases, documentation, or project resources.
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Python materials for the online course on diffusion models by @huggingface.
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HushMic is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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"building applications with LLMs through composability".
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A framework for elegantly configuring complex applications.
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Hydra is a code project with source, releases, documentation, or setup notes.
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Platform for deploying your Machine Learning to production.