Mastering Algorithms with Python
Год издания: 2025
Автор: Chenyang Shi
Издательство: Apress
ISBN: 979-8-8688-1799-1
Язык: Английский
Формат: EPUB
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 293
Gain a solid understanding of algorithms and improve your problem-solving abilities using Python code. With practical examples and clear explanations, this book bridges the gap between dense academic texts and overly simple industry guides.
Focusing on the logic behind essential algorithms such as Breadth First Search (BFS), Depth First Search (DFS), Divide-and-Conquer, Greedy Methods, and Dynamic Programming, the book provides ample examples, from easy to more advanced. By connecting these concepts to real-world examples, such as chess strategies and the Seam Carving, the book helps readers better grasp and apply algorithms. Each chapter also includes fully implemented Python code, making it a practical reference.
Mastering Algorithms with Python is ideal for IT professionals looking to enhance their skills and approach algorithms with clarity and confidence.
The computer algorithms are the bedrock for the success of any IT professionals (software engineers or data scientists alike), yet they seem intimidating for many at first glance. They are intimidating because they are not easy and often cleverly designed. Simply memorizing the pseudocode/code is a recipe for frustration. Also, the fact that there are so many different algorithms often overwhelms the newcomers. I, like many others, realized the importance of algorithms quite early and have gone through various learning practices such as solving (thousands of) coding problems at online judge websites, taking university algorithm classes, and reading algorithm books written by university professors and industry experts. Despite all these efforts, it was a bit strange that I still felt “not good enough on algorithms.” It is this feeling that urges me to reflect on how to find an effective way of learning algorithms.
First, we need to acknowledge that algorithms are many and we cannot learn all of them. Instead, we should master the classic ones, which are the foundations for other modern or complex algorithms. We need to really understand the classic ones. Rote memorization leads nowhere. The academic algorithm books are great resources, but, in my experience, sometimes they tend to be too abstract and concise to follow. In contrast, some industry books are either oversimplified or just display the code snippets without explaining how they are come up with.
This book aims to bridge that gap. It covers major classic algorithms such as Greedy, Dynamic Programming, Breadth-First Search, and Depth-First Search, relates them to daily objects, and explains them from the ground-up. Real-life examples such as chess or business travels help the readers build intuition gradually with concrete examples. All algorithms are implemented in Python from scratch which can be used as future references.
There is no shortcut for mastering the algorithms. However, learning them with a fun yet easy-to-follow resource will make this journey pleasant – that is the purpose of the book.
What You Will Learn:
· Understand foundational algorithms such as BFS, DFS, Divide-and-Conquer, Greedy Methods, Dynamic Programming through practical examples
· Implement algorithms in Python with step-by-step guidance and fully functional code for future reference
· Build a solid foundation in advanced concepts such as Minimum Spanning Trees, Fast Fourier Transform, and Monte Carlo Tree Search
· Quickly review Python essentials, including data types, flow control, generators, decorators, and classes to enhance your algorithmic understanding
Год издания: 2025
Автор: Chenyang Shi
Издательство: Apress
ISBN: 979-8-8688-1799-1
Язык: Английский
Формат: EPUB
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 293
Gain a solid understanding of algorithms and improve your problem-solving abilities using Python code. With practical examples and clear explanations, this book bridges the gap between dense academic texts and overly simple industry guides.
Focusing on the logic behind essential algorithms such as Breadth First Search (BFS), Depth First Search (DFS), Divide-and-Conquer, Greedy Methods, and Dynamic Programming, the book provides ample examples, from easy to more advanced. By connecting these concepts to real-world examples, such as chess strategies and the Seam Carving, the book helps readers better grasp and apply algorithms. Each chapter also includes fully implemented Python code, making it a practical reference.
Mastering Algorithms with Python is ideal for IT professionals looking to enhance their skills and approach algorithms with clarity and confidence.
The computer algorithms are the bedrock for the success of any IT professionals (software engineers or data scientists alike), yet they seem intimidating for many at first glance. They are intimidating because they are not easy and often cleverly designed. Simply memorizing the pseudocode/code is a recipe for frustration. Also, the fact that there are so many different algorithms often overwhelms the newcomers. I, like many others, realized the importance of algorithms quite early and have gone through various learning practices such as solving (thousands of) coding problems at online judge websites, taking university algorithm classes, and reading algorithm books written by university professors and industry experts. Despite all these efforts, it was a bit strange that I still felt “not good enough on algorithms.” It is this feeling that urges me to reflect on how to find an effective way of learning algorithms.
First, we need to acknowledge that algorithms are many and we cannot learn all of them. Instead, we should master the classic ones, which are the foundations for other modern or complex algorithms. We need to really understand the classic ones. Rote memorization leads nowhere. The academic algorithm books are great resources, but, in my experience, sometimes they tend to be too abstract and concise to follow. In contrast, some industry books are either oversimplified or just display the code snippets without explaining how they are come up with.
This book aims to bridge that gap. It covers major classic algorithms such as Greedy, Dynamic Programming, Breadth-First Search, and Depth-First Search, relates them to daily objects, and explains them from the ground-up. Real-life examples such as chess or business travels help the readers build intuition gradually with concrete examples. All algorithms are implemented in Python from scratch which can be used as future references.
There is no shortcut for mastering the algorithms. However, learning them with a fun yet easy-to-follow resource will make this journey pleasant – that is the purpose of the book.
What You Will Learn:
· Understand foundational algorithms such as BFS, DFS, Divide-and-Conquer, Greedy Methods, Dynamic Programming through practical examples
· Implement algorithms in Python with step-by-step guidance and fully functional code for future reference
· Build a solid foundation in advanced concepts such as Minimum Spanning Trees, Fast Fourier Transform, and Monte Carlo Tree Search
· Quickly review Python essentials, including data types, flow control, generators, decorators, and classes to enhance your algorithmic understanding
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