Machine Learning
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A collection of implementations and illustrative code accompanying DeepMind's published research papers across AI and scientific domains.
A collection of pre-trained machine learning models ported to TensorFlow.js for use directly in the browser or Node.js.
A Python library for augmenting images and associated data (heatmaps, keypoints, bounding boxes) for machine learning projects.
A comprehensive Python library for natural language processing, providing modules, datasets, and tutorials for NLP research and development.
A low-level tensor library for machine learning with integer quantization, automatic differentiation, and zero runtime allocations.
A machine-learning conversational dialog engine for creating chatbots in Python with language-independent training.
A simple Python framework for state-of-the-art natural language processing (NLP) tasks like named entity recognition and sentiment analysis.
A simple Python framework for state-of-the-art natural language processing (NLP) tasks like named entity recognition and sentiment analysis.
A modern C++ toolkit for machine learning, computer vision, and data analysis applications.
A curated list of awesome big data frameworks, resources, and tools across various categories.
A Python package for deep learning on graphs, framework-agnostic and optimized for performance and scalability.
A comprehensive JVM-based deep learning ecosystem for building, training, and deploying models with support for model import and distributed training.
A hyperparameter optimization framework for machine learning with a define-by-run API for dynamic search spaces.
Generate comprehensive data quality profiling and exploratory data analysis reports for Pandas and Spark DataFrames with a single line of code.
An open-source library for rapid development of software dealing with 3D data, with support for C++ and Python.
Generate comprehensive data quality profiles and exploratory data analysis reports for Pandas and Spark DataFrames with a single line of code.
A curated list of must-use resources for AI engineering, including books, courses, papers, frameworks, and tools.
A curated collection of must-use resources for AI engineering, including books, courses, papers, frameworks, and tools.
A reliable PyTorch implementation of reinforcement learning algorithms for research and industry.
A free and open-source network discovery and security auditing tool for mapping networks and identifying services.
A curated list of open-source large language models licensed for commercial use, including models for general text and code generation.
A drop-in replacement for the MNIST dataset, featuring 70,000 Zalando fashion article images for benchmarking machine learning algorithms.
An open source machine learning server for developers and data scientists, supporting event collection, algorithm deployment, and REST API queries.
A comprehensive study plan and resource collection for preparing for machine learning engineering interviews at top tech companies.
Generate 3D objects from text descriptions or images using conditional implicit functions.
A Python library that explains predictions of any machine learning classifier using local interpretable model-agnostic explanations.
A curated list of modern Generative AI projects, services, models, and resources across text, image, video, audio, and coding.
A standard Python API for single-agent reinforcement learning environments with a collection of reference environments and utilities.
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 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.
An open-source LLMOps platform unifying gateway, observability, evaluation, optimization, and experimentation for industrial-grade LLM applications.
A differentiable computer vision library for PyTorch, providing geometric vision and image processing algorithms for AI workflows.
A Python library for building custom machine learning models for tasks like image classification, object detection, and recommendations.
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