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The Hundred-Page Machine Learning Book


This book covers supervised and unsupervised learning, support vector machines, neural networks, ensemble methods, gradient descent, cluster analysis and dimensionality reduction, autoencoders and transfer learning, feature engineering and hyperparameter tuning.



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By Andriy Burkov, Author of The Hundred-Page Machine Learning Book

Burkov 100p Machine Learning Book
This long-awaited day has finally come and I'm proud and happy to announce that The Hundred-Page Machine Learning Book is now available to order on Amazon in a high-quality color paperback edition as well as a Kindle edition.

For the last three months, I worked hard to write a book that will make a difference. I firmly believe that I succeeded. I'm so sure about that because I received dozens of positive feedback. Both from readers who just start in artificial intelligence and from respected industry leaders.

I'm extremely proud that such best-selling AI book authors and talented scientists as Peter Norvig and Aurélien Géron endorsed my book and wrote the texts for its back cover and that Gareth James wrote the Foreword.

Here are several testimonials:

Peter Norvig, Research Director at Google, co-author of the best-selling textbook AIMA: "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 Geron, Senior AI Engineer, author of a 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.''

To know more about the book, please visit its website: themlbook.com.


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