The Hundred-Page Machine Learning Book

The Hundred-Page Machine Learning Book

ISBN:978-1-9995795-0-0 定价:USD 45.00

Everything you really need to know in Machine Learning in a hundred pages.
This is the first of its kind "read first, buy later" book. You can find the book online, read it, and then come back to pay for it if you liked the book or found it useful for your work, business or studies.
Review
"This book provides a great practical guide to get started and execute on ML within a few days without necessarily knowing much about ML apriori. The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue. A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time going through a formal degree program."--Deepak Agarwal, VP of Artificial Intelligence at LinkedIn
"This book is a great introduction to machine learning from a world-class practitioner and LinkedIn superstar Andriy Burkov. He managed to find a good balance between the math of the algorithms, intuitive visualizations, and easy-to-read explanations. This book will benefit the newcomers to the field as a thorough introduction to the fundamentals of machine learning, while the experienced professionals will definitely enjoy the practical recommendations from Andriy's rich experience in the field."--Karolis Urbonas, Head of Data Science at Amazon
"I wish such a book existed when I was a statistics graduate student trying to learn about machine learning. There is the right amount of math which demystify the centerpiece of an algorithm with succinct but very clear descriptions. I'm also impressed by the widespread coverage and good choices of important methods as an introductory book (not all machine learning books mention things like learning to rank or metric learning). Highly recommended to STEM major students."--Chao Han, VP, Head of R&D at Lucidworks
"This book provides a great practical guide to get started and execute on ML within a few days without necessarily knowing much about ML apriori. The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue. A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time going through a formal degree program."--Sujeet Varakhedi, Head of Engineering at eBay
"The Hundred-Page Machine Learning Book is an excellent read to get started with Machine Learning. In his book, Andriy Burkov distills the ubiquitous material on Machine Learning into concise and well-balanced intuitive, theoretical and practical elements that bring beginners, managers, and practitioners many life hacks."--Vincent Pollet, Head of Research at Nuance
作者介绍
Andriy Burkov is a dad of two and a machine learning expert based in Quebec City, Canada. Nine years ago, he got a Ph.D. in Artificial Intelligence, and for the last six years, he's been leading a team of machine learning developers at Gartner.
His specialty is natural language processing. His team works on building state-of-the-art multilingual text extraction and normalization systems for production, using both shallow and deep learning technologies.
内容简介
Released Drafts of the Chapters
Preface
Chapter 1: Introduction
Part I: Supervised Learning
Chapter 2: Notation and Definitions
Chapter 3: Fundamental Algorithms
Chapter 4: Anatomy of a Learning Algorithm
Chapter 5: Basic Practice
Chapter 6: Neural Networks and Deep Learning
Chapter 7: Problems and Solutions
Chapter 8: Advanced Practice
Part II: Unsupervised and Other Forms of Learning
Chapter 9: Unsupervised Learning
Chapter 10: Other Forms of Learning
Chapter 11: Conclusion