ML for Builders

This book starts where most projects actually begin: with a messy table, a deadline, and the need to ship something that works. The fastest way to get there in Python is a rhythm you’ll repeat on every problem: load data, shape it with NumPy and Pandas, fit a scikit-learn baseline, measure the right thing, and then let the results tell you whether your next improvement should come from the data, the features, or the model. This chapter is that rhythm without ceremony: just enough structure to keep you honest and fast.