文件名称：Interpretable Machine Learning
文件大小：10.03MB
文件格式：PDF
更新时间：2022-02-19 21:56:27
machine lear 机器学习
This book explains to you how to make (supervised) machine learning models interpretable. The chapters contain some mathematical formulas, but you should be able to understand the ideas behind the methods even without the formulas. This book is not for people trying to learn machine learning from scratch. If you are new to machine learning, there are a lot of books and other resources to learn the basics. I recommend the book “The Elements of Statistical Learning” by Hastie, Tibshirani, and Friedman (2009) 1 and Andrew Ng’s “Machine Learning” online course on the online learning platform coursera.com to start with machine learning.