Machine Learning Engineering Open Book
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Updated
Feb 21, 2026 - Python
Machine Learning Engineering Open Book
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 curated list of awesome MLOps tools
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
Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng
Frouros: an open-source Python library for drift detection in machine learning systems.
Decoding ML articles hub: Hands-on articles with code on production-grade ML
A comprehensive solution for monitoring your AI models in production
A robust () and fast () MLOps tool for managing data and pipelines in Rust ()
Tutorials on how to engineer Machine Learning projects using Deep Neural Networks with PyTorch and Python
My repo for the Machine Learning Engineering bootcamp 2022 by DataTalks.Club
A Helm chart containing Kubeflow Pipelines as a standalone service.
Machine Learning for Production Specialization
End-to-end Email Spam Detection system using Machine Learning and NLP, featuring TF-IDF, Logistic Regression, threshold optimization, and a FastAPI-based real-time inference API.
This repository contains examples of using various libraries/tools for MLOps.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
End-to-end ML project for tabular data.
Fruits Classification App (Gradio)
ML System - Model Deployment & Lifecycle Management
Fruits Classification App (Streamlit)
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