Overview
- Covers basic concepts like its unique features, data types, operators, and developing simple programs
- Includes data access and manipulation from standard file formats such as CSV, Excel, and JSON files
- Provides required knowledge and skill in coding and serves as the basis for developing machine learningapplications
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Table of contents (15 chapters)
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Front Matter
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Back Matter
Keywords
About this book
The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in data science. This book aims to help the readers understand the basic and advanced concepts for developing simple programs and the fundamentals required for building machine learning models. The book covers basic concepts like data types, operators, and statements that enable the reader to solve simple problems. As functions are the core of any programming, a detailed illustration of defining & invoking functions and recursive functions is covered. Built-in data structures of Python, such as strings, lists, tuples, sets, and dictionary structures, are discussed in detail with examples and exercise problems. Files are an integrated part of programming when dealing with large data. File handling operations are illustrated with examples and a case study at the end of the chapter. Widely used Python packages for data science, such as Pandas, Data Visualization libraries, and regular expressions, are discussed with examples and case studies at the end of the chapters. The book also contains a chapter on SQLite3, a small relational database management system of Python, to understand how to create and manage databases. As AI applications are becoming popular for developing intelligent solutions to various problems, the book includes chapters on Machine Learning and Deep Learning. They cover the basic concepts, example applications, and case studies using popular frameworks such as SKLearn and Keras on public datasets
Authors and Affiliations
About the authors
Muddana A Lakshmi received a Ph.D. in Computer Science and Engineering from Osmania University, Hyderabad. She is currently a professor in the Department of Computer Science and Engineering at GITAM Deemed to be University, Hyderabad, India. She has been in academics, teaching undergraduate and postgraduate students and guiding research scholars in the areas of Deep Learning and Security.
Sandhya Vinayakam received a Ph.D. in Computer Science and Engineering from Osmania University, Hyderabad. She is currently in the Department of Computer Science and Engineering at GITAM Deemed to be University, Hyderabad, India. She has been in academics and doing research in the areas of Image Processing and Deep Learning.
Bibliographic Information
Book Title: Python for Data Science
Authors: A. Lakshmi Muddana, Sandhya Vinayakam
DOI: https://doi.org/10.1007/978-3-031-52473-8
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 2024
Hardcover ISBN: 978-3-031-52472-1Published: 19 April 2024
Softcover ISBN: 978-3-031-52475-2Due: 20 May 2024
eBook ISBN: 978-3-031-52473-8Published: 18 April 2024
Edition Number: 1
Number of Pages: XVII, 392
Number of Illustrations: 92 b/w illustrations, 3 illustrations in colour
Topics: Data Structures and Information Theory, Artificial Intelligence, Python