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