Tags: #machine-learning

A unified framework for scaling AI and Python applications from a laptop to a cluster, providing a distributed runtime and AI libraries.

A unified framework providing state-of-the-art machine learning models for text, vision, audio, and multimodal tasks, optimized for both inference and training.

Provides sample code, notebooks, and resources for building and managing generative AI workflows on Google Cloud using Vertex AI and Gemini.

An open-source AI engineering platform for managing the complete lifecycle of AI applications, including agents, LLMs, and ML models, from debugging and evaluation to monitoring and optimization.

A unified and efficient framework for fine-tuning over 100 large language models (LLMs) and vision-language models (VLMs) with both CLI and Web UI.

A deep learning framework that simplifies PyTorch development by automating boilerplate engineering code, enabling scalable training from CPU to multi-node GPUs with minimal code changes.

An open-source framework for training multi-step LLM agents using reinforcement learning (GRPO) to learn from experience, offering a serverless RL training service.

A comprehensive open-source repository housing diverse research code and datasets from Google Research.

A free and open-source framework designed for efficient and flexible fine-tuning of large language models.

A human-centric Python framework for building, managing, and deploying real-life AI/ML systems from rapid prototyping to reliable production.

An industrial-strength Python library for advanced Natural Language Processing, designed for building real-world applications.

A comprehensive, step-by-step guide and codebase for building a ChatGPT-like Large Language Model from scratch using PyTorch.

A universal viewer for neural network, deep learning, and machine learning models, supporting a wide array of formats.

An open standard and format for machine learning models, enabling interoperability across AI frameworks and streamlining the path from research to production.

A comprehensive online course from Hugging Face designed to teach the fundamentals and advanced concepts of building AI agents using LLMs and popular frameworks.

A comprehensive repository offering over 50 tutorials and implementations for Generative AI agent techniques, from basic conversational bots to complex multi-agent systems.

A comprehensive repository showcasing advanced Retrieval-Augmented Generation (RAG) techniques through detailed, practical notebook tutorials.

A comprehensive open-source library providing AI agents with the skills to autonomously conduct the entire AI research lifecycle, from ideation to paper writing.

KServe is a standardized, scalable, and multi-framework platform for deploying and serving both generative and predictive AI models on Kubernetes.

An open-source, cloud-native vector database enabling semantic search at scale by combining vector similarity with structured filtering and integrated AI models.

Qdrant is a high-performance, massive-scale vector database and search engine designed for next-generation AI applications.

A container-native workflow engine for orchestrating parallel jobs and multi-step tasks on Kubernetes.

An open-source, multi-type data labeling and annotation tool designed to prepare and improve datasets for machine learning models.

A meticulously curated list of battle-tested, production-proven open-source AI models, libraries, infrastructure, and developer tools.

Kubeflow Pipelines is a Kubernetes-native platform for building, deploying, and managing end-to-end machine learning workflows.

A curated list of open-source libraries for deploying, monitoring, versioning, scaling, and securing machine learning models in production.

A collection of Jupyter notebooks and a new Python SDK demonstrating how to build, train, and deploy machine learning models on Amazon SageMaker.

A comprehensive MLOps platform for managing, orchestrating, and scaling the entire machine learning and deep learning lifecycle.

An open-source feature store that streamlines the management and serving of features for AI/ML models, ensuring consistency between training and inference.

A comprehensive, curated list of essential MLOps tools and resources, categorized to streamline the machine learning operations workflow.

Build machine learning models from natural language prompts using an AI-powered agentic approach.

A comprehensive educational platform for mastering the development, deployment, and iteration of production-grade machine learning applications.

A comprehensive, cloud-native, one-stop platform for machine learning, deep learning, and large language model development, covering the entire MLOps lifecycle.

A meticulously curated list of battle-tested, production-proven open-source AI models, libraries, infrastructure, and developer tools.

An AI agent platform designed to automate high-value research and development processes for data and models, driving data-driven AI.

A meticulously curated list of modern Generative Artificial Intelligence projects and services, offering a structured overview of the rapidly evolving AI landscape.

A comprehensive repository offering practical implementations of over 17 state-of-the-art AI agent architectures using LangChain and LangGraph.

A comprehensive 12-week, 24-lesson curriculum designed to introduce beginners to the fundamentals of Artificial Intelligence.

A comprehensive and curated list of the best LLMOps tools, designed to help developers navigate the complex landscape of Large Language Model operations.

A comprehensive repository offering C++ and Python code examples for computer vision, deep learning, and AI research, complementing articles on LearnOpenCV.com.

A comprehensive toolkit providing best practices and implementations for building, evaluating, and operationalizing recommendation systems.

A lightweight library providing a vast hub of ready-to-use datasets and efficient tools for data manipulation in AI and machine learning workflows.

A high-performance AI data platform for real-time search, recommendation, and machine learning inference at any scale.

A comprehensive collection of Jupyter Notebooks and sample applications designed to help users learn and experiment with Pinecone vector databases and common AI patterns.

A Python library for representing, transmitting, storing, and retrieving multimodal data, designed for AI applications.

A comprehensive repository offering practical implementations and evaluation guidance for advanced and agentic Retrieval-Augmented Generation (RAG) techniques.

A high-performance, scalable JAX-based open-source library for training large language models on Google Cloud TPUs and GPUs.

A user-friendly, versatile fine-tuning kit for image, video, and audio diffusion models, emphasizing simplicity and cutting-edge features.

A comprehensive, one-stop solution for training various Diffusion models, offering extensive features for fine-tuning, dataset preparation, and model management.

A streamlined tool to accelerate the fine-tuning process for multimodal models like Florence-2, PaliGemma 2, and Qwen2.5-VL.

xTuring simplifies the fine-tuning, evaluation, and deployment of open-source Large Language Models (LLMs) on private data, ensuring privacy and efficiency.

Enables efficient fine-tuning of LLMs, Vision, Audio, and OCR models on Apple Silicon Macs with an Unsloth-compatible API.

A comprehensive collection of PyTorch implementations for over 60 deep learning papers, accompanied by detailed side-by-side notes for enhanced understanding.

Provides Google Colab notebooks to easily run Stable Diffusion WebUI, including various models and extensions, though it is now outdated and superseded by TostUI.

A comprehensive open-source textbook and code repository dedicated to Reinforcement Learning from Human Feedback (RLHF) and post-training language models.

A continually updated, curated list of essential resources for Reinforcement Learning with Human Feedback (RLHF), encompassing research papers, codebases, datasets, and related materials.

A modular open-source framework for training constrained value-aligned Large Language Models (LLMs) using Safe Reinforcement Learning from Human Feedback (RLHF).

A comprehensive collection of recipes and code for training various reward models crucial for Reinforcement Learning from Human Feedback (RLHF) in large language models.

Docta is an advanced data-centric AI platform that detects and rectifies issues in various data types to improve model performance.

FinGPT is an open-source initiative providing cost-effective and rapidly adaptable large language models specifically designed for the dynamic financial sector.

Extends ComfyUI with advanced custom nodes for the LTX-2 video generation model, enabling powerful text-to-video and image-to-video workflows.

A comprehensive collection and categorization of diffusion model papers, accompanied by a detailed survey and taxonomy.

Applio is a powerful, user-friendly, and high-performance open-source tool for high-quality voice transformation.

An open-source Text-to-Speech system built on the VITS2 backbone, enhanced with multilingual BERT for improved speech synthesis.

A comprehensive repository offering roadmaps, projects, use cases, and interview preparation materials for mastering Generative AI.

MTEB is a comprehensive benchmark and evaluation framework designed to assess the performance of text embedding models and retrieval systems across a wide range of tasks.

A comprehensive Python library offering 60+ anomaly detectors for multi-modal data, featuring an agentic workflow for AI agents and benchmark-backed orchestration.

A comprehensive toolkit for computing CLIP embeddings and building scalable multimodal semantic search systems.

An open-source MLOps and AI orchestration platform for building, managing, and automating continuous machine learning and generative AI applications across their entire lifecycle.

PostgresML integrates machine learning and AI capabilities, including GPU acceleration and large language models, directly into PostgreSQL, eliminating the need for separate systems and data transfers.

A comprehensive, curated collection of free resources for learning AI, Machine Learning, LLMs, and AI Engineering from scratch.

A deep learning library for advanced Text-to-Speech generation, offering high-quality speech synthesis with pretrained models and multi-language support.

An efficient command-line tool to download, resize, and package vast collections of image URLs into ready-to-use datasets for machine learning.

A lightweight, pure C/C++ inference engine for various diffusion models, enabling efficient image and video generation across multiple platforms and hardware.

A comprehensive repository offering expert-level tutorials, guides, and courses on various Generative AI technologies, primarily focusing on Stable Diffusion and its ecosystem.

A comprehensive, open-source repository of Data Science learning resources and tools for real-world problem-solving.