ML
Machine learning algorithms implemented by pure numpy
C++ implementation of the Python Numpy library
Deep Learning Library. For education. Based on pure Numpy. Support CNN, RNN, LSTM, GRU etc.
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
NumPy aware dynamic Python compiler using LLVM
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Efficiently computes derivatives of NumPy code.
Technical Analysis Library using Pandas and Numpy
Extremely simple yet powerful header-only C++ plotting library built on the popular matplotlib
NumPy tutorials & educational content in notebook format
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
🦜🔗 Build context-aware reasoning applications
🦜🔗 Build context-aware reasoning applications 🦜🔗
AI PDF chatbot agent built with LangChain & LangGraph
A Roadmap to Becoming an AI Engineer — From Zero to AI Engineer 👨🏻🚀 🚀
Roadmap to becoming an Artificial Intelligence Expert in 2022