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Expert C++

You're reading from   Expert C++ Become a proficient programmer by learning coding best practices with C++17 and C++20's latest features

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Product type Paperback
Published in Aug 2023
Publisher Packt
ISBN-13 9781804617830
Length 604 pages
Edition 2nd Edition
Languages
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Authors (5):
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Araks Tigranyan Araks Tigranyan
Author Profile Icon Araks Tigranyan
Araks Tigranyan
Shunguang Wu Shunguang Wu
Author Profile Icon Shunguang Wu
Shunguang Wu
John Asatryan John Asatryan
Author Profile Icon John Asatryan
John Asatryan
Marcelo Guerra Hahn Marcelo Guerra Hahn
Author Profile Icon Marcelo Guerra Hahn
Marcelo Guerra Hahn
Vardan Grigoryan Vardan Grigoryan
Author Profile Icon Vardan Grigoryan
Vardan Grigoryan
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Toc

Table of Contents (24) Chapters Close

Preface 1. Part 1:Under the Hood of C++ Programming
2. Chapter 1: Building C++ Applications FREE CHAPTER 3. Chapter 2: Beyond Object-Oriented Programming 4. Chapter 3: Understanding and Designing Templates 5. Chapter 4: Template Meta Programming 6. Chapter 5: Memory Management and Smart Pointers 7. Part 2: Designing Robust and Efficient Applications
8. Chapter 6: Digging into Data Structures and Algorithms in STL 9. Chapter 7: Advanced Data Structures 10. Chapter 8: Functional Programming 11. Chapter 9: Concurrency and Multithreading 12. Chapter 10: Designing Concurrent Data Structures 13. Chapter 11: Designing World-Ready Applications 14. Chapter 12: Incorporating Design Patterns in C++ Applications 15. Chapter 13: Networking and Security 16. Chapter 14: Debugging and Testing 17. Chapter 15: Large-Scale Application Design 18. Part 3:C++ in the AI World
19. Chapter 16: Understanding and Using C++ in Machine Learning Tasks 20. Chapter 17: Using C++ in Data Science 21. Chapter 18: Designing and Implementing a Data Analysis Framework 22. Index 23. Other Books You May Enjoy

Data capturing and manipulation

Data capturing and manipulation are critical areas of data science. They involve the acquisition, extraction, transformation, and processing of data so that it is helpful for analysis and decision-making. These techniques are important in gaining meaningful insights and taking advantage of large, complex datasets. In this article, we will explore the importance of data capture and manipulation and discuss the basic concepts and techniques of these techniques.

Data capture refers to collecting and retrieving data from various sources. This can include structured data from databases, spreadsheets, or APIs and unstructured data from text, images, and social media sources. The data capture phase involves identifying the right start, extracting data, and converting it into a format suitable for analysis. Techniques such as web scraping, data extraction tools, and data integration frameworks are often used to capture and aggregate data from various sources...

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