Machine Learning Engineering in Action

Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production.

In Machine Learning Engineering in Action, you will learn:

Evaluating data science problems to find the most effective solution
Scoping a machine learning project for usage expectations and budget
Process techniques that minimize wasted effort and speed up production
Assessing a project using standardized prototyping work and statistical ...