Hands-on Train and Deploy ML
A hands-on tutorial for training and deploying a machine learning model as a serverless REST API to predict cryptocurrency prices.
What is Hands-on Train and Deploy ML?
Hands-on Train and Deploy ML is a tutorial project that guides developers through training a machine learning model to predict cryptocurrency prices and deploying it as a serverless REST API. It solves the problem of bridging the gap between experimental ML in notebooks and production-ready systems by teaching MLOps frameworks and tools. The project provides a complete, reproducible workflow for model development and deployment.
Machine learning engineers and data scientists who want to learn how to build and deploy ML systems beyond notebooks, focusing on production MLOps practices.
Developers choose this for its practical, step-by-step approach to real-world ML deployment using a modern, serverless stack. It uniquely combines experiment tracking, serverless API deployment, and automation in a single, hands-on tutorial.
Overview
Train and Deploy an ML REST API to predict crypto prices, in 10 steps
Use Cases
Best For
- Learning end-to-end MLOps workflows for model deployment
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