03743nam a22005295i 4500 978-3-031-52473-8 DE-He213 20251030111824.0 cr nn 008mamaa 240418s2024 sz | s |||| 0|eng d 9783031524738 978-3-031-52473-8 10.1007/978-3-031-52473-8 doi Q336 UN bicssc COM021000 bisacsh UN thema Muddana, A. Lakshmi. author. aut http://id.loc.gov/vocabulary/relators/aut 75360 Python for Data Science [electronic resource] / by A. Lakshmi Muddana, Sandhya Vinayakam. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XVII, 392 p. 95 illus., 3 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Representation of Discrete Signals and Systems -- The z-transform Analysis of Discrete Time Systems -- Discrete Fourier Transform and Computation -- Design of IIR Digital Filters -- Design of Finite Impulse Response (FIR) Digital Filters -- Digital Signal Processor -- Index. 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. Artificial intelligence Data processing. Python (Computer program language). 64608 Artificial intelligence. 58441 Data Science. Python. 47553 Artificial Intelligence. 58441 Vinayakam, Sandhya. author. aut http://id.loc.gov/vocabulary/relators/aut 75361 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031524721 Printed edition: 9783031524745 Printed edition: 9783031524752 https://doi.org/10.1007/978-3-031-52473-8 ZDB-2-SCS ZDB-2-SXCS 59205 59205