Overview
- This textbook focuses on the most essential elements and practically useful techniques in Machine Learning
- Strikes a balance between the theory of Machine Learning and implementation in Python
- Supplemented by exercises, serves as a self-sufficient book for readers with no Python programming experience
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Table of contents (15 chapters)
Keywords
About this book
The textbook covers a range of topics including nearest neighbors, linear models, decision trees, ensemble learning, model evaluation and selection, dimensionality reduction, assembling various learning stages, clustering, and deep learning along with an introduction to fundamental Python packages for data science and machine learning such as NumPy, Pandas, Matplotlib, Scikit-Learn, XGBoost, and Keras with TensorFlow backend.
Given the current dominant role of the Python programming language for machine learning, the book complements the theoretical presentation of each technique by its Python implementation. In this regard, two chapters are devoted to cover necessary Python programming skills. This feature makes the book self-sufficient for students with different programming backgrounds and is in sharp contrast with other books in the field that assume readers have prior Python programming experience. As such, the systematic structure of the book, along with the many examples and exercises presented, will help the readers to better grasp the content and be equipped with the practical skills required in day-to-day machine learning applications.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Machine Learning with Python
Book Subtitle: Theory and Implementation
Authors: Amin Zollanvari
DOI: https://doi.org/10.1007/978-3-031-33342-2
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-33341-5Published: 12 July 2023
Softcover ISBN: 978-3-031-33344-6Due: 15 September 2023
eBook ISBN: 978-3-031-33342-2Published: 11 July 2023
Edition Number: 1
Number of Pages: XVII, 452
Topics: Machine Learning, Python, Data Structures and Information Theory, Artificial Intelligence, Pattern Recognition