Object-Oriented Approach to Problem Solving and Machine Learning with Python

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A01=Maha Hadid
A01=Mohammad Amin Kuhail
A01=Shahbano Farooq
A01=Sujith Samuel Mathew
advanced Python OOP for data science
Aggregation
Association
Author_Maha Hadid
Author_Mohammad Amin Kuhail
Author_Shahbano Farooq
Author_Sujith Samuel Mathew
Category=PBW
Category=UB
Category=UMB
Category=UMN
Category=UMX
Category=UMZ
Category=UYQ
Class Diagrams
Composition
computational linguistics
Encapsulation
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
exception handling strategies
GUI
Inheritance
Machine Learning
NLP
Object Serialization
Object-Oriented Analysis
Object-Oriented Design
Object-Oriented Programming
Pandas
Pickle
Polymorphism
Python
Sentiment Analysis
supervised learning
text mining techniques
Tkinter interface design
Twitter Data Analysis
UML
unsupervised algorithms
Use Case Diagrams

Product details

  • ISBN 9781032668314
  • Weight: 580g
  • Dimensions: 178 x 254mm
  • Publication Date: 11 May 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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This book is a comprehensive guide suitable for beginners and experienced developers alike. It teaches readers how to master object-oriented programming (OOP) with Python and use it in real-world applications.

Start by solidifying your OOP foundation with clear explanations of core concepts such as use cases and class diagrams. This book goes beyond theory as you get practical examples with well-documented source code available in the book and on GitHub.

This book doesn’t stop at the basics. Explore how OOP empowers fields such as data persistence, graphical user interfaces (GUIs), machine learning, and data science, including social media analysis. Learn about machine learning algorithms for classification, regression, and unsupervised learning, putting you at the forefront of AI innovation.

Each chapter is designed for hands-on learning. You’ll solidify your understanding with case studies, exercises, and projects that apply your newfound knowledge to real-world scenarios. The progressive structure ensures mastery, with each chapter building on the previous one, reinforced by exercises and projects.

Numerous code examples and access to the source code enhance your learning experience. This book is your one-stop shop for mastering OOP with Python and venturing into the exciting world of machine learning and data science.

Sujith Samuel Mathew holds a PhD in computer science from the University of Adelaide, Australia. He is an associate professor at Zayed University, UAE. He specializes in ubiquitous and distributed computing, focusing on the Internet of Things and related Smart City applications.

Mohammad Amin Kuhail holds an MSc in software engineering from the University of York and a PhD in software development from IT University of Copenhagen. He is an associate professor at Zayed University, specializing in human–computer interaction and software engineering, and he researches chatbot technology, user behavior, and education.

Maha Hadid holds an MSc in Information Sciences and Systems from the University of Marseille in France. She is an instructor at Zayed University, UAE, with experience in undergraduate courses and instructional design and delivery for blended and classroom-based courses.

Shahbano Farooq holds an MSc in computer science from the University of Calgary. She is an instructor at Zayed University, UAE, specializing in human-computer interaction and machine learning.

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