As its title says, it's the hundred-page machine learning book. I can't claim to have fully grasped all concepts on a first reading, but I will happily return to this in due course. Leanpub requires cookies in order to provide you the best experience. Just a moment while we sign you in to your Goodreads account. I had quite a lot econometric background before starting the book but was not familiar with many of the machine-learning methods described. You could read it in a day. His economy of exposition, his inclusion of the necessary mathematical underpinnings, and his succinct and pragmatic tone overall are much appreciated.Burkov's book deserves to be on every machine learning professional and enthusiast's desk. It takes two days to complete and becomes a reference book to me now.If I have to describe that book, that would be with the following scene:If I have to describe that book, that would be with the following scene:Absolutely great book to dabble in everything machine learning related. The Hundred-Page Machine Learning Book is an excellent read to get started with Machine Learning. If you like books and love to build cool products, we may be looking for you. Leanpub requires cookies in order to provide you the best experience. I have no comparison to other books in this area, but I think that the Burkov's book is a great introduction to machine learning for people who would like to develop related skills (and it is not very long :)). This repository contains the draft PDF copies of the book: The 100 Page Machine Learning Book He managed to find a good balance between the math of the algorithms, intuitive visualizations, and easy-to-read explanations.
Absolutely great book to dabble in everything machine learning related. Leanpub is a powerful platform for serious authors, combining a simple, elegant writing and publishing workflow with a store focused on selling in-progress ebooks. If you have some basic concepts this book provides very good introduction to the field. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together.
Practitioners with experience will use this book as a collection of pointers to the directions of further self-improvement.The book also comes in handy when brainstorming at the beginning of a project, when you try to answer the question whether a given technical or business problem is "machine-learnable" and, if yes, which techniques you should try to solve it.This book is a great introduction to machine learning from a world-class practitioner and LinkedIn superstar Andriy Burkov. Although its very technical for someone who is not a computer savant its a start. Was amazing to see how the project grown and took momentum. A beginner in machine learning will find in this book just enough details to get a comfortable level of understanding of the field and start asking the right questions.
Leanpub is a powerful platform for serious authors, combining a simple, elegant writing and publishing workflow with a store focused on selling in-progress ebooks. As its title says, it's the hundred-page machine learning book.
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.I wish such a book existed when I was a statistics graduate student trying to learn about machine learning.
Andriy Burkov’s “The Hundred-Page Machine Learning Book” became a mandatory reading for software engineers in our Data Science company the second day I received my copy.
To avoid buying counterfeit on Amazon, click on "See All Buying Options" and choose "Amazon.com" and not a third-party seller.Burkov's book deserves to be on every machine learning professional and enthusiast's desk. It also allows you to further investigate the topics of your interest with the use of QR codes. T...WARNING! Start by marking “The Hundred-Page Machine Learning Book” as Want to Read:
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