As its title says, it's the hundred-page machine learning book. It was written by an expert in machine learning holding a Ph.D. in Artificial Intelligence with almost two decades of industry experience in computer science and hands-on machine learning.
This is a unique book in many aspects. It is the first successful attempt to write an easy to read book on machine learning that isn't afraid of using math. It's also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.
The book contains only those parts of the huge body of material on machine learning developed since the 1960s that have proven to have a significant practical value. A beginner in machine learning will find in this book just enough details to get a comfortable level of understanding of the field and start asking the right questions. Practitioners with experience will use this book as a collection of pointers to the directions of further self-improvement.
The book also comes in handy when brainstorming at the beginning of a project, when you try to answer the question whether a given technical or business problem is "machine-learnable" and, if yes, which techniques you should try to solve it.
The book comes with a wiki which contains pages that extend some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources. Thanks to the continuously updated wiki this book like a good wine keeps getting better after you buy it.
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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.
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