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The Hundred-Page Machine Learning Book by [Burkov, Andriy]

The Hundred-Page Machine Learning Book [Print Replica] Kindle Edition

4.5 out of 5 stars 2 customer reviews

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Review

"Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics--both theory and practice--that will be useful to practitioners, and for the reader who understands that this as the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field." -- Peter Norvig, Research Director at Google, author of the most popular artificial intelligence textbook in the world Artificial Intelligence: A Modern Approach

"The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn't hesitate to go into the math equations: that's one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field." -- Aurélien Géron, Senior Artificial Intelligence Engineer, author of a #1 Amazon bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow

"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 or professionals who are interested to get started with machine learning for their analytics projects or preparing for data science interviews." -- Chao Han, VP, Head of R&D at Lucidworks

"Whether you want to become a machine learning practitioner or looking for an everyday resource, Andriy's book does a fantastic job of cutting the noise and hitting the tracks and full speed from the first page. It manages to structure all the important concepts from foundations to applications into a relatively quick read and leave the reader engaged at all times. " -- Sujeet Varakhedi, Head of Engineering at eBay

"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​

Product Description

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Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world: "Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics — both theory and practice — that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field."

Aurélien Géron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: "The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn't hesitate to go into the math equations: that's one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field."

Karolis Urbonas, Head of Data Science at Amazon: "A great introduction to machine learning from a world-class practitioner."

Chao Han, VP, Head of R&D at Lucidworks: "I wish such a book existed when I was a statistics graduate student trying to learn about machine learning."

Sujeet Varakhedi, Head of Engineering at eBay: "Andriy's book does a fantastic job of cutting the noise and hitting the tracks and full speed from the first page.''

Deepak Agarwal, VP of Artificial Intelligence at LinkedIn: "A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time.''

Vincent Pollet, Head of Research at Nuance: "The Hundred-Page Machine Learning Book is an excellent read to get started with Machine Learning.''

Gareth James, Professor of Data Sciences and Operations, co-author of the bestseller An Introduction to Statistical Learning, with Applications in R: "This is a compact “how to do data science” manual and I predict it will become a go-to resource for academics and practitioners alike. At 100 pages (or a little more), the book is short enough to read in a single sitting. Yet, despite its length, it covers all the major machine learning approaches, ranging from classical linear and logistic regression, through to modern support vector machines, deep learning, boosting, and random forests. There is also no shortage of details on the various approaches and the interested reader can gain further information on any particular method via the innovative companion book wiki. The book does not assume any high level mathematical or statistical training or even programming experience, so should be accessible to almost anyone willing to invest the time to learn about these methods. It should certainly be required reading for anyone starting a PhD program in this area and will serve as a useful reference as they progress further. Finally, the book illustrates some of the algorithms using Python code, one of the most popular coding languages for machine learning. I would highly recommend “The Hundred-Page Machine Learning Book” for both the beginner looking to learn more about machine learning and the experienced practitioner seeking to extend their knowledge base."

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.

Product details

  • Format: Kindle Edition
  • File Size: 11778 KB
  • Print Length: 158 pages
  • Simultaneous Device Usage: Unlimited
  • Publisher: Andriy Burkov (12 January 2019)
  • Sold by: Amazon Australia Services, Inc.
  • Language: English
  • ASIN: B07MGCNKXB
  • Text-to-Speech: Not enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Enhanced Typesetting: Not Enabled
  • Average Customer Review: 4.5 out of 5 stars 2 customer reviews
  • Amazon Bestsellers Rank: #58,751 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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2 customer reviews

4.5 out of 5 stars

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21 March 2019
Format: PaperbackVerified Purchase
19 May 2019
Format: Paperback

Most helpful customer reviews on Amazon.com

Amazon.com: 4.7 out of 5 stars 111 reviews
Leonard B.
5.0 out of 5 starsSoftware engineers, this is the machine learning book you need
18 January 2019 - Published on Amazon.com
Format: PaperbackVerified Purchase
41 people found this helpful.
Sandro Skansi
5.0 out of 5 starsExcellent handbook for data science managers, great for almost everybody else
18 February 2019 - Published on Amazon.com
Format: PaperbackVerified Purchase
17 people found this helpful.
Michael Sprayberry
5.0 out of 5 starsGreat overview of machine learning
27 January 2019 - Published on Amazon.com
Verified Purchase
12 people found this helpful.
Kelvin Sundli
5.0 out of 5 starsThis book kicks you in the right direction
24 January 2019 - Published on Amazon.com
Format: PaperbackVerified Purchase
10 people found this helpful.
bobdc
5.0 out of 5 starsExcellent for learning and as a reference book
22 March 2019 - Published on Amazon.com
Format: PaperbackVerified Purchase
5 people found this helpful.