lakshmi muddana (6 Ergebnisse)

Soft cover. Zustand: New. Contents: 1 Basic Python 2 Functions 3 Strings 4 Built-in Data Structures: Lists 5 Built-in Data Structure: Tuple 6 Built-in Data Structure: Sets 7 Built-in Data Structure: Dictionary 8 Files 9 Data Manipulations with Pandas 10 SQLite3 11 Regular Expressions 12 Data Visualizations, AppendixA, Appendix B, Index. The book covers basic concepts like its unique features, data types, operators, and developing simple programs using selection and loop statements. As functions are the core of any programming, a detailed illustration of defining & invoking functions, parameter passing techniques, and recursive functions are covered. Built-in data structures of Python like strings, lists, tuples, sets, and dictionary structures are discussed in detail with examples and programming problems. File handling is an important task when handling large data. Data access and manipulation from standard file formats such as CSV, Excel, and JSON files are included in the book. Python being widely used in Data Analytics & Machine Learning, Pandas dataframes, visualizations, and regular expressions are covered in detail with examples. Every chapter includes illustrations with examples, worked-out problems, multiple choice questions for knowledge testing, and exercise problems for practice. The book is supported by a solution manual to multiple-choice questions and exercise problems. The aim and scope of the book are to provide the required knowledge and skill in coding. The book serves as the basis for developing Machine learning applications.

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Taschenbuch. Zustand: Neu. Python for Data Science | A. Lakshmi Muddana (u. a.) | Taschenbuch | xvii | Englisch | 2025 | Springer | EAN 9783031524752 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Hardcover. Zustand: Brand New. 409 pages. 9.26x6.11x9.21 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.