A Julia package for fitting (statistical) mixed-effects models.
A collaboration platform where the machine learning community shares models, datasets and applications. It hosts public models, datasets and Spaces, and offers an open source stack including libraries such as Transformers, Datasets and Accelerate. It also provides paid Compute and Enterprise solutions, with an Inference Providers API giving access to models from multiple AI providers.
Maige is open-source infrastructure for running natural language workflows on a codebase. After connecting a repository, users write rules describing what should happen when issues and pull requests are opened, and the tool can label, assign, comment, review code, and run simple code snippets. It works with the GitHub API. A standard plan is offered after free use, with usage-based payment.
Keras is a deep learning API that focuses on debugging speed, code conciseness and maintainability. It uses a multi-backend approach that allows work with JAX, TensorFlow and PyTorch, and the KerasHub library provides Keras 3 implementations of popular model architectures with pretrained checkpoints.
HandyAI is a collection of free browser-based tools for AI and Claude developers, including token counters, prompt analyzers, JSON to tool-use converters and cost calculators. It requires no sign-up and lists the LLM Token Counter and AI Cost Calculator as live tools, with others announced for later release.
GNU Octave is a programming language for scientific computing with mathematics-oriented syntax and built-in 2D/3D plotting and visualization tools. It is free software licensed under the GNU General Public License and runs on GNU/Linux, macOS, BSD, and Microsoft Windows. Its syntax is largely compatible with Matlab, and it can be extended by packages.
OCaml-GPR is an OCaml library for Gaussian process regression that includes a command line application and an example application. It implements approximation algorithms for scalable regression with arbitrary covariance functions.
Community notes
Be the first to share how this project worked for you.
Sign in with a verified account to leave a review or join the discussion.
Sign in to reviewKeep exploring
A collaboration platform where the machine learning community shares models, datasets and applications. It hosts public models, datasets and Spaces, and offers an open source stack including libraries such as Transformers, Datasets and Accelerate. It also provides paid Compute and Enterprise solutions, with an Inference Providers API giving access to models from multiple AI providers.
Maige is open-source infrastructure for running natural language workflows on a codebase. After connecting a repository, users write rules describing what should happen when issues and pull requests are opened, and the tool can label, assign, comment, review code, and run simple code snippets. It works with the GitHub API. A standard plan is offered after free use, with usage-based payment.
Keras is a deep learning API that focuses on debugging speed, code conciseness and maintainability. It uses a multi-backend approach that allows work with JAX, TensorFlow and PyTorch, and the KerasHub library provides Keras 3 implementations of popular model architectures with pretrained checkpoints.
HandyAI is a collection of free browser-based tools for AI and Claude developers, including token counters, prompt analyzers, JSON to tool-use converters and cost calculators. It requires no sign-up and lists the LLM Token Counter and AI Cost Calculator as live tools, with others announced for later release.
GNU Octave is a programming language for scientific computing with mathematics-oriented syntax and built-in 2D/3D plotting and visualization tools. It is free software licensed under the GNU General Public License and runs on GNU/Linux, macOS, BSD, and Microsoft Windows. Its syntax is largely compatible with Matlab, and it can be extended by packages.
OCaml-GPR is an OCaml library for Gaussian process regression that includes a command line application and an example application. It implements approximation algorithms for scalable regression with arbitrary covariance functions.
