The Python Workshop

11. Machine Learning

Overview

By the end of this chapter, you will be able to, apply machine learning algorithms to solve different problems; compare, contrast, and apply different types of machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, Naive Bayes, and AdaBoost; analyze overfitting and implement regularization; work with GridSearchCV and RandomizedSearchCV to adjust hyperparameters; evaluate algorithms using a confusion matrix and cross-validation and solve real-world problems using the machine learning algorithms outlined here.

Introduction

Computer algorithms enable machines to learn from data. The more data an algorithm receives, the more capable the algorithm is of detecting ...