Made with ML is a comprehensive learning platform focused on production-grade machine learning application development, with over 40,000 learners. The project provides complete development process guidance from machine learning experimentation to production deployment, serving as an authoritative resource for learning how to build reliable ML products.
Full-Stack ML Development Perspective
The project takes a full-stack approach to teaching machine learning application development, covering not only model training and optimization but also diving deep into data engineering, model deployment, monitoring, and operations skills essential for production environments. This comprehensive approach helps developers understand the complete lifecycle of ML product development.
Production-Grade Best Practices
The course particularly emphasizes software engineering best practices in ML development, including code version control, automated testing, CI/CD pipelines, and containerized deployment. Through these practices, developers can build stable, maintainable ML systems that meet enterprise-level application requirements.
Project-Driven Learning
The entire learning process revolves around a complete ML project, starting from data collection and preprocessing, through model development and validation, to automated deployment and continuous integration. This project-driven learning approach allows learners to gain real development experience.
Modern Technology Stack
The project utilizes mainstream technology stack in modern ML development, including PyTorch, Ray, MLflow, FastAPI, and other tools. By learning the practical application of these technologies, developers can master industry-standard development tools and methodologies, laying a solid foundation for career development.
