Machine Learning
Showing 36 of 1845 projects
A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
An open-source AI engineering platform for debugging, evaluating, monitoring, and optimizing production LLM applications and machine learning models.
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications in Python.
A curated list of the top 100 most cited deep learning papers from 2012-2016, serving as a foundational reading list.
A unified Python library for explaining any machine learning model's predictions using Shapley values from game theory.
Jupyter notebooks with example code and exercises from the first edition of Hands-on Machine Learning with Scikit-Learn and TensorFlow.
Generates bitmaps and tilemaps that are locally similar to a single input example, using a constraint-solving algorithm inspired by quantum mechanics.
The fastai book, published as Jupyter Notebooks, provides an introduction to deep learning, fastai, and PyTorch.
A fast, memory-efficient reimplementation of OpenAI's Whisper speech-to-text model using CTranslate2.
Python implementations of popular machine learning algorithms from scratch with interactive Jupyter demos and mathematical explanations.
An industrial deep learning framework from China supporting unified dynamic/static graphs, automatic parallelism, and integrated training/inference for large models.
An industrial deep learning framework supporting unified dynamic/static graphs, automatic parallelism, and integrated training/inference for large models.
A PyTorch library for building and training Graph Neural Networks (GNNs) on structured and irregular data.
A comprehensive library for building and training Graph Neural Networks (GNNs) with PyTorch.
Fast automatic speech recognition with accurate word-level timestamps and speaker diarization, built on OpenAI's Whisper.
A curated list of awesome computer vision resources, including papers, datasets, software, and courses.
A curated list of awesome computer vision resources, including papers, datasets, software, and tutorials.
A lightweight Python library for face recognition and facial attribute analysis (age, gender, emotion, race) with a unified API.
A community-driven repository tracking datasets and state-of-the-art results for common NLP tasks across multiple languages.
A reactive Python notebook that's reproducible, git-friendly, and deployable as scripts or apps.
A free, self-taught curriculum following undergraduate Data Science guidelines using MOOCs from top universities.
A repository of examples, utilities, and best practices for building and deploying production-ready recommendation systems.
An open-source platform for debugging, evaluating, and monitoring LLM applications, RAG systems, and agentic workflows.
A cross-platform, high-performance accelerator for machine learning inference and training with ONNX models.
An open-source AI memory tool that records your screen and audio locally, enabling search and automation agents based on your computer activity.
An open-source AI memory tool that captures your screen and audio locally, enabling search and automation agents based on your computer activity.
An open standard format for representing machine learning models to enable interoperability between frameworks.
Open source machine learning framework for building contextual text- and voice-based chatbots and assistants.
An open-source framework for financial large language models, enabling cost-effective fine-tuning for tasks like sentiment analysis and forecasting.
A minimalist, high-performance machine learning framework for Rust with a focus on serverless inference and GPU support.
A curated list of awesome open-source libraries for deploying, monitoring, versioning, and scaling production machine learning systems.
A curated list of awesome open-source libraries for deploying, monitoring, versioning, and scaling production machine learning systems.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
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