Our reading notes

Machine Learning Crash Course

Course by Google

Modular ML lessons on regression, classification, data preparation, overfitting, neural networks, embeddings, and production systems.

What to look for

01
Use the data and generalization modules to evaluate a proposal’s assumptions.
02
The production and fairness modules broaden the conversation beyond model accuracy.

Keep in mind

A foundation course, not an end-to-end production architecture or a substitute for evaluating your own data.

Put it to work

Try this next

Choose the overfitting module, then ask how your next ML project will keep evaluation data separate from training data.

Get the data template

Notes and exercises by Awesome CTO. The original work belongs to Google.

Work through the bigger question.

Our data guide connects the reading to a practical approach and a template.