1.stas00 / ml-engineering
Machine Learning Engineering Open Book
Ranked by Attention Score: stars gained over the last 30 complete days
47 repositories by Attention Score · Oct 4, 2026 – Nov 2, 2026 (UTC)
Machine Learning Engineering Open Book
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
The absolute trainer to light up AI agents.
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Learn how to develop, deploy and iterate on production-grade ML applications.
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
An orchestration platform for the development, production, and observation of data assets.
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Workflow Engine for Kubernetes
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Always know what to expect from your data.
Build, Manage and Deploy AI/ML Systems
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
The Open Source Feature Store for AI/ML
Turns Data and AI algorithms into production-ready web applications in no time.
A curated list of references for MLOps
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dmls-book`
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
An open source DevOps tool from the CNCF for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI Artifact.
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
AI Infra / AI Orchestration / AI Control Plane
☁️ Build multimodal AI applications with cloud-native stack
TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
Superduper: End-to-end framework for building custom AI applications and agents.
🏕️ Reproducible development environment for humans and agents
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
Open Source Data Annotation & Labeling Tools
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
Hopsworks - Data-Intensive AI platform with a Feature Store
🦖 𝗟𝗲𝗮𝗿𝗻 about 𝗟𝗟𝗠𝘀, 𝗟𝗟𝗠𝗢𝗽𝘀, and 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀 for free by designing, training, and deploying a real-time financial advisor LLM system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 𝘷𝘪𝘥𝘦𝘰 & 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴
Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Kraken CI is a continuous integration and testing system.