Master machine learning through clarity, not complexity―in a book engineered to teach with exceptional conciseness.
Translated into 11 languages and used in thousands of universities worldwide, this book takes a unique approach: it assumes that your time is valuable. Instead of drowning you in theory or skimming the surface, it delivers a complete education in modern machine learning, focusing on what matters in practice. From fundamental algorithms that form the backbone of many applications, to cutting-edge deep learning and neural networks, you'll understand how these tools work and how to use them.
What sets this book apart is its careful progression through key concepts. You'll start with essential mathematical concepts and gradually progress through the most practically important machine learning algorithms. You'll learn practical skills like feature engineering, regularization, handling imbalanced datasets, ensembles, and model evaluation that help turn theory into working systems.
The book covers not just supervised learning, but also clustering, topic modeling, metric learning, learning to rank, and recommendation systems, giving you a complete toolkit for solving modern machine learning challenges.
This isn't just another theoretical textbook. Every chapter reflects the author's real-world experience, focusing on techniques that work in practice. Whether you're building a recommendation system, analyzing customer data, or working with images and text, you'll find practical guidance here.
This isn't a high-level overview either. The book explores each concept with precisely the right level of technical detail-enough to create those crucial "a-ha!" moments of understanding, but not so much that you get overwhelmed by mathematical notation or theoretical abstractions. It hits that sweet spot where complex ideas click into place naturally, making it valuable for both newcomers looking to build a strong foundation and experienced practitioners seeking to expand their toolkit.
What's Inside
About the Reader
The book assumes a basic foundation in college-level mathematics. However, it's entirely self-contained, introducing all necessary mathematical concepts through intuitive explanations. This approach ensures that readers with basic mathematical knowledge can follow along without getting lost in complex equations.
Endorsed by Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world, Aurélien Géron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, and other industry leaders.
Read endorsements on themlbook.com
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Andriy Burkov is the author of "The Hundred-Page Machine Learning Book" and "Machine Learning Engineering," both of which became #1 Best Sellers on Amazon. He holds a Ph.D. in Artificial Intelligence and is a recognized expert in machine learning and natural language processing.As a machine learning expert and leader, Andriy has successfully led dozens of production-grade AI projects in different business domains at Fujitsu and Gartner. His previous books have been translated into more than a dozen languages and are used as textbooks in many universities worldwide. His work has impacted millions of machine learning practitioners and researchers worldwide.Currently, Andriy is the Head of Machine Learning at TalentNeuron, where he develops AI solutions for talent marketplace analytics. He uses language models and other machine learning tools to analyze billions of job postings across 30+ languages in near real time.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Recycle Bookstore, San Jose, CA, Etats-Unis
Hardcover. Etat : Good. Cover has modest rubbing and smudging, otherwise looks bright and sharp. Spine slightly cocked, binding still strong. Pages have pen marks up to page 7, rest of pages are clean. Overall a solid reading copy. N° de réf. du vendeur 1045681
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Vendeur : World of Books (was SecondSale), Montgomery, IL, Etats-Unis
Etat : Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. N° de réf. du vendeur 00109012326
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Vendeur : World of Books Inc, Montgomery, IL, Etats-Unis
Hardback. Etat : Good. 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.Aur lien G ron, 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.''Gareth James, Professor of Data Sciences and Operations, co-author of the bestseller An Introduction to Statistical Learning, with Applications in R: 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. N° de réf. du vendeur CIN1999579518G
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Vendeur : Goodwill of Silicon Valley, SAN JOSE, CA, Etats-Unis
Etat : good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear. N° de réf. du vendeur GWSVV.1999579518.G
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Etat : New. N° de réf. du vendeur 36644947-n
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Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
Hardback or Cased Book. Etat : New. The Hundred-Page Machine Learning Book. Book. N° de réf. du vendeur BBS-9781999579517
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Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 36644947
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Vendeur : Rarewaves USA, HEBRON, KY, Etats-Unis
Hardback. Etat : New. Hard Cover ed. N° de réf. du vendeur LU-9781999579517
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Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
HRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur IG-9781999579517
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Vendeur : California Books, Miami, FL, Etats-Unis
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