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Applied Computational Thinking with Python

You're reading from   Applied Computational Thinking with Python Algorithm design for complex real-world problems

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781837632305
Length 438 pages
Edition 2nd Edition
Languages
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Authors (2):
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Sofía De  Jesús Sofía De Jesús
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Sofía De Jesús
 Martinez Martinez
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Martinez
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Toc

Table of Contents (25) Chapters Close

Preface 1. Part 1: An Introduction to Computational Thinking
2. Chapter 1: Fundamentals of Computer Science FREE CHAPTER 3. Chapter 2: Elements of Computational Thinking 4. Chapter 3: Understanding Algorithms and Algorithmic Thinking 5. Chapter 4: Understanding Logical Reasoning 6. Chapter 5: Errors 7. Chapter 6: Exploring Problem Analysis 8. Chapter 7: Designing Solutions and Solution Processes 9. Chapter 8: Identifying Challenges within Solutions 10. Part 2: Applying Python and Computational Thinking
11. Chapter 9: Introduction to Python 12. Chapter 10: Understanding Input and Output to Design a Solution Algorithm 13. Chapter 11: Control Flow 14. Chapter 12: Using Computational Thinking and Python in Simple Challenges 15. Chapter 13: Debugging 16. Part 3: Data Processing, Analysis, and Applications Using Computational Thinking and Python
17. Chapter 14: Using Python in Experimental and Data Analysis Problems 18. Chapter 15: Introduction to Machine Learning 19. Chapter 16: Using Computational Thinking and Python in Statistical Analysis 20. Chapter 17: Applied Computational Thinking Problems 21. Chapter 18: Advanced Applied Computational Thinking Problems 22. Chapter 19: Integrating Python with Amazon Web Services (AWS) 23. Index 24. Other Books You May Enjoy

Problem 8 – using Python to create a CNN

In this section, we will explore a problem that involves artificial intelligence (AI). To be more specific, we will focus on building a CNN. But what exactly is a CNN? Well, a CNN is a deep learning algorithm that operates on images as its input. It processes and assigns importance to various aspects of the image based on predetermined features.

The following diagram illustrates the process involved in a CNN:

Figure 18.25: CNN process

Figure 18.25: CNN process

A CNN is created to simplify how we categorize the images without sacrificing accuracy in terms of the predictions we want to be able to get from our image analyses. It’s like if we were applying a filter. Once we apply the filter, we can see the characteristics. The preceding diagram shows a simplified schematic for this process.

The problem we’re going to be diving into is handwriting training and analysis. Thinking about the computational thinking process...

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