| ISBN13: | 9781032668338 |
| ISBN10: | 1032668334 |
| Binding: | Hardback |
| No. of pages: | 314 pages |
| Size: | 254x178 mm |
| Weight: | 453 g |
| Language: | English |
| Illustrations: | 37 Illustrations, black & white; 66 Illustrations, color; 5 Halftones, color; 37 Line drawings, black & white; 61 Line drawings, color; 19 Tables, black & white |
| 700 |
The Object-Oriented Approach to Problem Solving and Machine Learning with Python
GBP 89.99
Click here to subscribe.
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.
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.
Chapter 1 Introduction to Object-Oriented Programming
Chapter 2 Python Data Structures
Chapter 3 Exception Handling
Chapter 4 Fundamentals of Object-Oriented Analysis
Chapter 5 Fundamentals of Object-Oriented Design
Chapter 6 File Handling, Object Serialization, and Data Persistence
Chapter 7 Graphical User Interface with Tkinter
Chapter 8 Machine Learning with Python
Chapter 9 Natural Language Processing and Text Mining with Python
Appendix A Installing Python and Environment Setup
Appendix B Choosing an IDE
Appendix C Debugging Your Python Program
Appendix D PEP Style Guide-Coding Standard and Conventions
