machine learning this covers forms of machine learning beyond classification and regression formal evaluation procedures for machinelearning models preparing data for deep learning feature engineering tackling overfitting the universal workflow for approaching machinelearning problems after the three practical examples in you should be starting to feel familiar with how to approach classification and regression problems using neural networksand you've witnessed the central problem of machine learningoverfitting this will formalize some of your new intuition into solid conceptual framework for attacking and solving deep-learning problems we'll consolidate all of these concepts--model evaluationdata preprocessing and feature engineeringand tackling overfitting--into detailed seven-step workflow for tackling any machine-learning task licensed to