The Mathematics of Machine Learning in Vernacular

A very simple and basic machine learning popular science book. The text uses the form of dialogue QA to explain the mathematical problems in machine learning in an easy-to-understand manner, especially some of the questions you want to ask. It explains basic issues very clearly with appropriate examples. It is a relatively relaxing and enjoyable introductory book for students who have never understood machine learning and have almost forgotten mathematics. For students who have basic knowledge, just treat it as fun and relax!

I have always felt that everything related to machines is about esoteric and complicated things, but in the book, the author explains machine learning in a simple and easy-to-understand way. The analysis is clear and clear, and it is expressed in easy-to-understand language, making it easier to understand. It is the savior of many patients with mathematical learning difficulties. The combination of theory and application can allow readers to deepen their understanding and recognition. In this era of science and technology informing development, machine learning will also be an important topic in the future and deserves attention.

Machine learning is an important topic in today's computer and mathematics circles. The content of this book mainly includes mathematical knowledge commonly used in machine learning, such as linear algebra, probability theory, statistics, etc. At the same time, the book also introduces some mathematical principles of machine learning algorithms, such as support vector machines, decision trees, etc. By reading this book, readers can understand the mathematical knowledge needed in machine learning and its application scenarios in machine learning. This book is also a good introductory textbook that can help you quickly master the required mathematical knowledge and apply it to machine learning.

I have learned more or less advanced mathematics and Python before in college and at work. Python was even a required course in college before. I read this book to review the knowledge I had learned before. After studying it, I still feel that I know more advanced mathematics than Python [face covering]. There are also two heroines in it, one is playful and the other is sharp-tongued (not), which I find quite interesting [laughs].

This book is very interesting. It explains the mathematical knowledge of machine learning in a conversational way, which is easy to understand. I particularly liked the parts about regression and classification problems in the book, which gave me a better understanding of the practical application of mathematical formulas through specific cases. Moreover, the book also introduces the practical experience of some data scientists, which is very inspiring to me. Recommended to friends who are interested in machine learning!

The author Kengo Tateishi is a machine learning engineer at SmartNews. After graduating from Saga University in Japan, he worked for several development companies. The company he worked for was in the data analysis and machine learning team established in Fukuoka, Japan. He was responsible for using machine learning to develop products such as recommendation systems and text classification, and served as the team leader. , This book uses a dialogue between Ayano, a programmer who is learning machine learning, and her friend Mio, and uses a logical organization to combine specific problems of regression and classification to provide readers with an in-depth explanation of practical mathematical basics in machine learning.

It is a practical book that even I, who am completely new to machine learning and mathematics, can understand. A book in which the author explains the mathematical concepts and methods involved in machine learning in a concise and easy-to-understand manner. It focuses on providing readers with an intuitive understanding of the mathematical foundations required for machine learning, avoiding the use of overly abstract and complex mathematical formulas and derivation, so as to better help readers easily understand the principles and applications of machine learning algorithms.

Wow, I love this book. It can guide readers to learn in easy-to-understand words. Not bad, I like it very much.

Books that allow people to understand knowledge are good books.