Description As its title says, it\'s the Hundred-Page Machine Learning book.
Thanks to the continuously updated wiki this Book like a good wine keeps getting better after you buy 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.
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.
Practitioners with experience will use this Book as a collection of pointers to the directions of further self-improvement.
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.
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.
It\'s also the first attempt to squeeze a wide range of Machine Learning topics in a systematic way and without loss in quality.
It is the first successful attempt to write an easy to read Book on Machine Learning that isn\'t afraid of using math.
This is a unique Book in many aspects. in Artificial Intelligence with almost two decades of industry experience in computer science and hands-on Machine learning.
It was written by an expert in Machine Learning holding a Ph.
D.
Description As its title says, it\'s the Hundred-Page Machine Learning book
