Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Experiment tracking, model registries, feature stores, workflow schedulers and deployment tooling.
Signals: mlops, machine-learning-operations, experiment-tracking, model-registry, feature-store, ml-platform, kubeflow, mlflow
202 results
Run your deep learning workloads on Kubernetes more easily and efficiently.
Host repository for the "Reproducible Deep Learning" PhD course
Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022
Collection of reproducible deep learning for compressive sensing
Deep Learning Experiment Management
Example deep learning projects that use wandb's features.
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
全语言制品仓库，涵盖npm、Maven、PyPi、Docker、Gradle、SBT、Cocoapods、Swift、RPM、Debian、PHP、Go、Pub、Ivy、NuGet、Conda、Cargo、Conan、Yarn、GitLFS、Helm、OHPM等主流工具,涵盖Huggingface 等主流AI模型仓库的代理与同步
🤖 MLE-Agent: Your intelligent companion for seamless AI engineering and research. 🔍 Integrate with arxiv and paper with code to provide better code/research plans 🧰 OpenAI, Anthropic, Gemini, Ollama, etc supported. :fireworks: Code RAG
Run all your local AI together in one package - Ollama, Supabase, n8n, Open WebUI, and more!
🏕️ Reproducible development environment for humans and agents
nannyml: post-deployment data science in python
Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.
☁️ Build multimodal AI applications with cloud-native stack
Turn expensive prompts into cheap fine-tuned models
Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.
🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴
The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features
Hopsworks - Data-Intensive AI platform with a Feature Store
All the available resources to master MLOPS from scratch
No description
🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴
🤖Self-Modifying Framework from the Future 🔮 World's First AMS
24,540 repositories in the index in total.
