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  • Book Overview & Buying Applied Computational Thinking with Python
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Applied Computational Thinking with Python

Applied Computational Thinking with Python - Second Edition

By : Sofía De Jesús, Dayrene Martinez
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Applied Computational Thinking with Python

Applied Computational Thinking with Python

By: Sofía De Jesús, Dayrene Martinez

Overview of this book

Computational thinking helps you to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that you should possess to keep ahead of the curve in this modern era of information technology. Developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence. This book begins by helping you get to grips with decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design, along with teaching you how to apply these elements practically while designing solutions for challenging problems. You’ll then learn about various techniques involved in problem analysis, logical reasoning, algorithm design, clusters and classification, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions. Toward the end, you will discover how to identify pitfalls in the solution design process and how to choose the right functionalities to create the best possible algorithmic solutions. By the end of this algorithm book, you will have gained the confidence to successfully apply computational thinking techniques to software development.
Table of Contents (25 chapters)
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1
Part 1: An Introduction to Computational Thinking
10
Part 2: Applying Python and Computational Thinking
16
Part 3: Data Processing, Analysis, and Applications Using Computational Thinking and Python

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

Abstract data types (ADTs) 22

abstraction 29, 32, 88

Adam optimization algorithm 270

additional problems, computational thinking 36

budget, planning 36

savings and interest 37-39

advanced applied computational thinking problems

algorithm and data visual representations 354-357

Python, used for analyzing data for specific populations 350

Python, used for analyzing genetic data 365-369

Python, used for analyzing stocks 370-374

Python, used for creating CNN 374-379

Python, used for creating housing data models 353, 354

Python, used for creating tessellations 342-346

Python, used for language detection 357, 358

Python, used in biological data analysis 346-349

specific problem, defining for analyzing and identifying population 350-353

algebraic coding theory...

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83
Tech Concepts
36
Programming languages
73
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Applied Computational Thinking with Python
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