Intelligence at LinkedIn: "A wonderful book for engineers who want to incorporate ML in their dayto-day. At pages or a little more , the book is short enough to. Yet, despite its length, it covers all the major machine learning approaches,. 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 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 or actually pages you will read, not the last, provides a solid introduction to the field. 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.
At 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. Don't forget to subscribe to the mailing list if you wish to receive updates! Already above 16, subscribers! User Tools Register Log In.
Site Tools Search. Enjoy your reading! Join the Mailing List. Chapter 1: Introduction. Chapter 2: Notation and Definitions. Chapter 3: Fundamental Algorithms plus in-depth material. All you need to know about Machine Learning in a hundred pages 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!
Is This Book For You? Is this book for you? You will enjoy the book if you are: a software engineer or a scientist who wants to become a machine learning engineer or a data scientist a data scientist trying to stay on the edge of the state-of-the-art and deepen their ML expertise a manager who wants to feel confident while talking about AI with engineers and product people a curious person looking to find out how machine learning works and maybe build something new What Industry Leaders Say.
Testimonials What industry leaders say. 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 spending an enormous amount of time. 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. What the internet says.
Book's features concise and to the point — the book can be read during a week. About the author. Andriy Burkov Hey! My name is Andriy. I'm a dad of two and a machine learning expert based in Quebec City, Canada. Nine years ago, I got a Ph. My specialty is natural language processing. My team works on building state-of-the-art multilingual text extraction and normalization systems for production, using both shallow and deep learning technologies.
Reach me on LinkedIn , Twitter or email. Subscribe to the mailing list.
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