Numerical Machine Learning
by: Zhiyuan Wang (Author), Sayed Ameenuddin Irfan (Author), Christopher Teoh (Author), Priyanka Hriday Bhoyar (Author)
ASIN: B0CH2NN4MZ
Publisher finelybook 出版社: Bentham Science Publishers (August 29, 2023)
Language 语言: English
Print Length 页数: 224 pages
ISBN-10: 9815136992
ISBN-13: 9789815136999
Book Description
Numerical Machine Learning is a simple textbook on machine learning that bridges the gap between mathematics theory and practice. The book uses numerical examples with small datasets and simple Python codes to provide a complete walkthrough of the underlying mathematical steps of seven commonly used machine learning algorithms and techniques, including linear regression, regularization, logistic regression, decision trees, gradient boosting, Support Vector Machine, and K-means Clustering.
Through a step-by-step exploration of concrete numerical examples, the students (primarily undergraduate and graduate students studying machine learning) can develop a well-rounded understanding of these algorithms, gain an in-depth knowledge of how the mathematics relates to the implementation and performance of the algorithms, and be better equipped to apply them to practical problems.
Key features
-Provides a concise introduction to numerical concepts in machine learning in simple terms
-Explains the 7 basic mathematical techniques used in machine learning problems, with over 60 illustrations and tables
-Focuses on numerical examples while using small datasets for easy learning
-Includes simple Python codes
-Includes bibliographic references for advanced reading
The text is essential for college and university-level students who are required to understand the fundamentals of machine learning in their courses.
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