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Machine Learning Zoomcamp is an open-source repository containing the materials for a comprehensive course that teaches machine learning engineering from fundamentals to deployment. The project is designed to guide learners through the complete lifecycle of developing machine learning systems, starting with data preparation and model training and ending with production deployment. Participants learn how to build regression and classification models using Python libraries such as NumPy, Pandas, and Scikit-learn. The course also introduces more advanced topics including decision trees, ensemble methods, and neural networks. Later modules focus on practical engineering topics such as containerization with Docker, API development with FastAPI, and scaling machine learning services using Kubernetes and cloud platforms. The repository includes lecture materials, assignments, and projects that allow learners to gain hands-on experience implementing machine learning pipelines.
Features
- End-to-end machine learning engineering curriculum
- Hands-on assignments building regression and classification models
- Coverage of algorithms such as decision trees and ensemble methods
- Practical deployment using Docker and FastAPI
- Scaling machine learning services with Kubernetes and cloud tools
- Project-based learning with real-world ML engineering workflows
Project Samples
