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Data science and machine learning using python / Reema Thareja

By: Thareja, ReemaMaterial type: TextTextPublisher: Chennai : McGraw Hill Education (India) Private Limited, © 2023Description: xviii, 621 pages : illustrations ; 28 cmISBN: 9789355322142Subject(s): Data science | Machine learning | PythonDDC classification: 005.133
Contents:
Preface Chapter 1: Basics of Python Programming Chapter 2: Data Structures in Python Chapter 3: Functions and Modules Chapter 4: Data Handling Using Numpy Chapter 5: Working with Panda Chapter 6: Plotting Graphs Chapter 7: File Handling Chapter 8: Interfacing Python With MYSQL Chapter 9: Introduction to Machine Learning Chapter 10: Regression Analysis in Machine Learning Chapter 11: Classification and Clustering Chapter 12: Advanced Learning
Summary: The objective of this book is to introduce the concepts of Python programming language in a lucid way so that the reader can easily use these concepts to perform data science and machine learning applications for solving real world problems. The book has been specifically written to serve as a textbook for undergraduate and postgraduate students. It can also be used by professionals who either wish to work in the area of Data Science and Machine Learning using Python or are already working in it. Every chapter in this book contains multiple programming examples to impart practically sound knowledge of the concept. To further enhance the understanding of the subject, there are numerous objective-type, subjective type and programming exercises at the end of each chapter. The book aims to impart sound understanding of concepts to acquaint the reader with the techniques and applications in the area. Written in a lucid language, all the concepts in this book are explained using numerous examples and programming exercises. Besides every topic, Programming Tips are given to make the reader aware of some typical errors or important concepts which we otherwise ignore. Key Features • The language is simple and easy to understand • Glossary of important terms at the end of each chapter • Comprehensive exercises for better clarity • Lots of executed programs for more practice • Appendices to give additional information
List(s) this item appears in: New Arrivals - August 1st to 31st 2023
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Books Institute of Public Enterprise, Library
S Campus
005.133 THA (Browse shelf) Checked out 12/13/2023 47687
Books Institute of Public Enterprise, Library
S Campus
005.133 THA (Browse shelf) Available 47688

Preface

Chapter 1: Basics of Python Programming
Chapter 2: Data Structures in Python
Chapter 3: Functions and Modules
Chapter 4: Data Handling Using Numpy
Chapter 5: Working with Panda
Chapter 6: Plotting Graphs
Chapter 7: File Handling
Chapter 8: Interfacing Python With MYSQL
Chapter 9: Introduction to Machine Learning
Chapter 10: Regression Analysis in Machine Learning
Chapter 11: Classification and Clustering
Chapter 12: Advanced Learning

The objective of this book is to introduce the concepts of Python programming language in a lucid way so that the reader can easily use these concepts to perform data science and machine learning applications for solving real world problems. The book has been specifically written to serve as a textbook for undergraduate and postgraduate students. It can also be used by professionals who either wish to work in the area of Data Science and Machine Learning using Python or are already working in it. Every chapter in this book contains multiple programming examples to impart practically sound knowledge of the concept. To further enhance the understanding of the subject, there are numerous objective-type, subjective type and programming exercises at the end of each chapter. The book aims to impart sound understanding of concepts to acquaint the reader with the techniques and applications in the area. Written in a lucid language, all the concepts in this book are explained using numerous examples and programming exercises. Besides every topic, Programming Tips are given to make the reader aware of some typical errors or important concepts which we otherwise ignore.


Key Features

• The language is simple and easy to understand
• Glossary of important terms at the end of each chapter
• Comprehensive exercises for better clarity
• Lots of executed programs for more practice
• Appendices to give additional information

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