Python for Data Science (Record no. 87873)

000 -LEADER
fixed length control field 03732nam a22005295i 4500
001 - CONTROL NUMBER
control field 978-3-031-52473-8
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730171907.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240418s2024 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031524738
-- 978-3-031-52473-8
082 04 - CLASSIFICATION NUMBER
Call Number 005.7
100 1# - AUTHOR NAME
Author Muddana, A. Lakshmi.
245 10 - TITLE STATEMENT
Title Python for Data Science
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVII, 392 p. 95 illus., 3 illus. in color.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 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.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Data processing.
700 1# - AUTHOR 2
Author 2 Vinayakam, Sandhya.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-52473-8
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer Nature Switzerland :
-- Imprint: Springer,
-- 2024.
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-- text
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337 ## -
-- computer
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-- rdamedia
338 ## -
-- online resource
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347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Python (Computer program language).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Python.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
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