Model-Based Machine Learning
- Available for pre-order. Item will ship after December 31, 2021
This book is unusual for a machine learning text book in that the authors do not review dozens of different algorithms. Instead they introduce all of the key ideas through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter therefore introduces one case study which is drawn from a real-world application that has been solved using a model-based approach.
Table of Contents
How Can Machine Learning Solve My Problem? A Murder Mystery. Assessing People's Skills. Meeting your Match. Uncluttering your Inbox. Recommender Case Study. Medical Case Study. Interlude: Probabilistic Programming. Crowdsourcing Case Study. Other People's Models.