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230249476
The Hundred-Page Machine Learning Book
Item #:
230249476
USD 74
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What Stands Out
Concise Overview
Offers a distilled summary of machine learning concepts, making it accessible for both beginners and professionals seeking a quick, comprehensive reference without overwhelming detail.
Practical Focus
Emphasizes practical applications and real-world scenarios, equipping readers with the tools to effectively implement machine learning techniques in various fields.
Clear Examples
Contains well-structured examples and illustrations, enhancing understanding and retention of complex topics, thus fostering a deeper grasp of machine learning methodologies.
Product Details
- WARNING! To avoid counterfeit, make sure that the book ships from and sold by Amazon. Avoid third-party sellers.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.
| Publisher | Andriy Burkov |
| Publication date | 13 Jan. 2019 |
| Language | English |
| Print length | 160 pages |
| ISBN-10 | 199957950X |
| ISBN-13 | 978-1999579500 |
| Item weight | 376 g |
| Dimensions | 19.05 x 0.97 x 23.5 cm |
| Part of series | The Hundred-Page Books |
Who Should Buy?
-
Beginners in ML
Ideal for novices seeking a concise introduction to machine learning concepts and algorithms without overwhelming details.
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Busy Professionals
Great for those needing a quick yet comprehensive overview of machine learning principles to enhance their skills efficiently.
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Students of Data Science
Perfect for students looking for a clear, structured resource to supplement their courses and deepen their understanding.
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Advanced Practitioners
Not suitable for experienced machine learning professionals seeking in-depth technical discussions or cutting-edge research findings.
Product Description
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AI & Machine Learning Editorial Review
The Hundred-Page Machine Learning Book is authored by Andriy Burkov and was published on January 13, 2019. This 160-page resource is crafted for those with a mathematical background who are looking to delve into machine learning. Reviewers appreciate its rigorous yet concise explanations and the way it clarifies complex notations and concepts. The book covers a range of topics from fundamental principles to practical algorithms, making it a vital tool for understanding machine learning theory and its applications. However, readers note that it may not be ideal for absolute beginners, as a foundational knowledge of machine learning would be beneficial.
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Pros
- Concise explanations of complex concepts
- Covers practical ML problems effectively
- Clarifies mathematical notations well
- Suitable for readers with some ML background
- Offers insights on unique ML techniques
Cons
- Content may be too dense for absolute beginners
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USD 74
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