Description
Book Synopsis: “Highly recommended to everyone interested in deepening their understanding of Python and practical computer science.” | Key Features > Master formal techniques taught in college computer science classes > Connect computer science theory to real-world applications, data, and performance > Prepare for programmer interviews > Recognize the core ideas behind most “new” challenges > Covers Python 3.7
Note: Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About The Book:
Programming problems that seem new or unique are usually rooted in well-known engineering principles. Classic Computer Science Problems in Python guides you through time-tested scenarios, exercises, and algorithms that will prepare you for the “new” problems you’ll face when you start your next project. In this amazing book, you'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. As you work through examples for web development, machine learning, and more, you'll remember important things you've forgotten and discover classic solutions that will save you hours of time.
What You Will Learn
- Search algorithms
- Common techniques for graphs
- Neural networks
- Genetic algorithms
- Adversarial search
This Book Is Written For
For intermediate Python programmers.
About The Author
David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont. He is the author of Dart for Absolute Beginners (Apress, 2014), Classic Computer Science Problems in Swift (Manning, 2018), and Classic Computer Science Problems in Java (Manning, 2020)
Table of Contents
- Small problems
- Search problems
- Constraint-satisfaction problems
- Graph problems
- Genetic algorithms
- K-means clustering
- Fairly simple neural networks
- Adversarial search
- Miscellaneous problems
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Details
Are you ready to take your Python programming skills to the next level? Look no further than Classic Computer Science Problems in Python! This highly recommended book is the ultimate guide for intermediate Python programmers who want to deepen their understanding of Python and practical computer science. With a focus on mastering formal techniques taught in college computer science classes, this book will help you connect computer science theory to real-world applications, data, and performance.
One of the key features of this book is its ability to prepare you for programmer interviews. It covers a wide range of coding challenges, from simple tasks like binary search algorithms to more complex problems like clustering data using k-means. By working through these examples and exercises, you'll not only remember important concepts but also discover classic solutions that can save you hours of time.
Whether you're interested in web development, machine learning, or other areas of computer science, Classic Computer Science Problems in Python has got you covered. It explores search algorithms, common techniques for graphs, neural networks, genetic algorithms, adversarial search, and more. The book even uses type hints throughout, making it a great resource for learning about this powerful Python feature.
Written by David Kopec, an assistant professor of Computer Science and Innovation, this book draws on his extensive experience and expertise in the subject. Kopec is also the author of other popular programming books, including Dart for Absolute Beginners and Classic Computer Science Problems in Java.
Don't miss out on this opportunity to enhance your Python skills and deepen your understanding of computer science. Purchase the print book today and receive a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Start your journey towards becoming a Python expert and tackle the "new" problems with confidence.
Read more about Classic Computer Science Problems in Python.
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