Machine Learning with Swift

What this book covers

Chapter 1, Getting Started with Machine Learning, teaches the main concepts of machine learning.

Chapter 2, Classification – Decision Tree Learning, builds our first machine learning application.

Chapter 3, K-Nearest Neighbors Classifier, continues exploring classification algorithms, and we learn about instance-based learning algorithms.

Chapter 4, K-Means Clustering, continues with instance-based algorithms, this time focusing on an unsupervised clustering task.

Chapter 5, Association Rule Learning, explores unsupervised learning more deeply. 

Chapter 6, Linear Regression and Gradient Descent, returns to supervised learning, but this time we switch our attention from non-parametric models, such as KNN and k-means, ...