Stage 1 · Lesson 6 of 8
One command to train, and a saved pipeline
Production training starts with one command that goes from raw data to a saved model with no manual steps: read config, load and split data, fix , fit, evaluate, save. Use a small command-line interface (CLI) with arguments for the data path and seed.
Save the whole preprocessing and model as one , not only the estimator, so serving applies exactly the same transformations. Know your formats: or pickle for , skops as a safer alternative, the framework's own format for PyTorch or XGBoost, and ONNX as a portable format. Never load a pickle from a source you do not trust, because loading it can run code.
Common trapsaving the model without its preprocessing, so the serving code rebuilds features by hand and gets them slightly wrong.
A question to check yourself, an AI practice session and 2 cheat sheet entries come with the full roadmap. Unlock
Resources for this stage
Start with· follow one of these
- CoursePaidGrokking Python Fundamentals
Design Gurus · Beginner · $50
If your Python stops at notebooks: modules, functions, classes and error handling done properly
- CourseFreeMade With ML
Goku Mohandas · Advanced
Free: the scripting, CLI, testing and documentation lessons turn notebook code into a real project