Machine Learning
Showing 36 of 1845 projects
A Python library that explains predictions of any machine learning classifier using local interpretable model-agnostic explanations.
A low-code declarative framework for building custom LLMs, neural networks, and other AI models with YAML configurations.
A low-code declarative framework for building custom LLMs, neural networks, and other AI models with YAML configurations.
An open-source LLMOps platform unifying gateway, observability, evaluation, optimization, and experimentation for industrial-grade LLM applications.
An open-source data-centric AI library for automatically detecting and fixing data quality issues in machine learning datasets.
A curated guide to learning machine learning with Python and Jupyter Notebook, featuring courses, notebooks, and practical resources.
A curated guide to learning machine learning with Python and Jupyter Notebook, featuring hands-on tutorials, courses, and ethical considerations.
A differentiable computer vision library for PyTorch, providing geometric vision and image processing algorithms for AI workflows.
A curated list of deep learning resources for computer vision, including papers, courses, books, and software.
A curated list of deep learning resources for computer vision, including papers, courses, books, and software.
A Python library for building custom machine learning models for tasks like image classification, object detection, and recommendations.
An ultra-performant data transformation framework for AI, with incremental processing and data lineage built-in.
A Python framework for creating reproducible, maintainable, and modular data engineering and data science pipelines.
Fast, state-of-the-art tokenizers for training and tokenization, optimized for both research and production.
A research framework for fast prototyping of reinforcement learning algorithms, designed for easy experimentation and reproducibility.
An elegant PyTorch-based deep reinforcement learning library with modular APIs for both research and application development.
An open-source inference serving platform for deploying AI models from multiple frameworks across cloud, data center, and edge devices.
Upload a photo of any room to generate AI-powered redesigns and variations using the ControlNet ML model.
A PyTorch implementation of YOLOv3 for real-time object detection, supporting export to ONNX, CoreML, and TFLite.
An automated machine learning library that trains and deploys high-accuracy models for tabular, text, image, and time series data with minimal code.
A framework for elegantly configuring complex applications, particularly in machine learning and research.
A practical booklet covering the four main steps of designing machine learning systems with 27 interview questions.
Code examples and tutorials for Stanford's TensorFlow for Deep Learning Research course (CS 20).
An open-source Python toolkit for speaker diarization with state-of-the-art pretrained models and pipelines.
A comprehensive resource of deep learning techniques and models for analyzing satellite and aerial imagery.
A curated repository of resources, datasets, and research papers for 3D machine learning, covering computer vision, graphics, and deep learning.
A deep reinforcement learning library offering high-quality, single-file implementations of algorithms like PPO, DQN, and SAC for research and education.
A community-driven collection of data science interview questions and answers covering theory, technical skills, and probability.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
A standardized, flexible project template for data science work using Cookiecutter to structure reproducible projects.
A TensorFlow 2 library providing simple, composable abstractions for machine learning research via the snt.Module concept.
A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
A curated list of resources dedicated to reinforcement learning, including theory, applications, code, tutorials, and platforms.
A curated list of reinforcement learning resources including theory, applications, code libraries, tutorials, and platforms.
A unified Python framework for machine learning with time series, offering scikit-learn compatible tools for forecasting, classification, clustering, and more.
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