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.
An ultra-performant data transformation framework for AI, with incremental processing and data lineage built-in.
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.
Fast, state-of-the-art tokenizers for training and tokenization, optimized for both research and production.
A Python framework for creating reproducible, maintainable, and modular data engineering and data science pipelines.
An open-source inference serving platform for deploying AI models from multiple frameworks across cloud, data center, and edge devices.
An elegant PyTorch-based deep reinforcement learning library with modular APIs for both research and application development.
A research framework for fast prototyping of reinforcement learning algorithms, designed for easy experimentation and reproducibility.
Upload a photo of any room to generate AI-powered redesigns and variations using the ControlNet ML model.
A framework for elegantly configuring complex applications, particularly in machine learning and research.
An automated machine learning library that trains and deploys high-accuracy models for tabular, text, image, and time series data with minimal code.
A PyTorch implementation of YOLOv3 for real-time object detection, supporting export to ONNX, CoreML, and TFLite.
A practical booklet covering the four main steps of designing machine learning systems with 27 interview questions.
An open-source Python toolkit for speaker diarization with state-of-the-art pretrained models and pipelines.
Code examples and tutorials for Stanford's TensorFlow for Deep Learning Research course (CS 20).
A deep reinforcement learning library offering high-quality, single-file implementations of algorithms like PPO, DQN, and SAC for research and education.
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 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 unified Python framework for machine learning with time series, offering scikit-learn compatible tools for forecasting, classification, clustering, and more.
A unified Python framework for machine learning with time series, offering scikit-learn compatible tools for forecasting, classification, clustering, and more.
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 TensorFlow 2 library providing simple, composable abstractions for machine learning research via the snt.Module concept.
A curated list of resources dedicated to reinforcement learning, including theory, applications, code, tutorials, and platforms.
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