Soft cover. Condition: 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.
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ISBN 10: 9394883274 ISBN 13: 9789394883277
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Published by Springer International Publishing AG, Cham, 2025
ISBN 10: 3031524756 ISBN 13: 9783031524752
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Paperback. Condition: new. Paperback. 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 The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in data science. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Ane Books Pvt. Ltd, 2025
ISBN 10: 9394883274 ISBN 13: 9789394883277
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Hardcover. Condition: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200113343 ISBN 13: 9786200113344
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Published by Springer International Publishing AG, 2024
ISBN 10: 3031524721 ISBN 13: 9783031524721
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Published by Springer International Publishing AG, Cham, 2025
ISBN 10: 3031524756 ISBN 13: 9783031524752
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Paperback. Condition: new. Paperback. 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 The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in data science. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Published by Springer International Publishing AG, 2024
ISBN 10: 3031524721 ISBN 13: 9783031524721
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ISBN 10: 3031524721 ISBN 13: 9783031524721
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Published by Springer International Publishing AG, 2024
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Taschenbuch. Condition: 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. Condition: 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.
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Published by Springer International Publishing AG, Cham, 2025
ISBN 10: 3031524756 ISBN 13: 9783031524752
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Paperback. Condition: new. Paperback. 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 The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in data science. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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ISBN 10: 3031524721 ISBN 13: 9783031524721
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Hardcover. Condition: Brand New. 409 pages. 9.26x6.11x9.21 inches. In Stock.
Buch. Condition: 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.
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Published by Ane Books India, 2010
ISBN 10: 9394883274 ISBN 13: 9789394883277
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ISBN 10: 9394883274 ISBN 13: 9789394883277
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Published by Springer, Springer Apr 2025, 2025
ISBN 10: 3031524756 ISBN 13: 9783031524752
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 412 pp. Englisch.
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Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200113343 ISBN 13: 9786200113344
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Aluvalu Dr.RajanikanthHaving functional experience of cloud computing, Bigdata Research and Education Management for more than 15 Years. Currently working as Associate Professor in the Dept of CSE, Vardhaman College of Engineering, H.
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Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200113343 ISBN 13: 9786200113344
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Published by Springer-Nature New York Inc, 2024
ISBN 10: 3031524721 ISBN 13: 9783031524721
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Published by Springer, Berlin, Springer Nature Switzerland, Ane Books Pvt. Ltd., Springer, 2024
ISBN 10: 3031524721 ISBN 13: 9783031524721
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 392 pp. Englisch.
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Published by Springer, Springer Apr 2025, 2025
ISBN 10: 3031524756 ISBN 13: 9783031524752
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 datasetsSpringer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 412 pp. Englisch.