10.1 Best Book - Cormen
When putting this course together, I relied on my favorite book on algorithms: Cormen "Introduction to Algorithms". This book is a textbook at MIT for Computer Science. Here's what its third edition looks like:
It's a classic book on algorithms, which is used in universities all around the globe. It covers a wide range of algorithms and data structures, including sorting, searching, graph algorithms, dynamic programming, and much more.
It also includes theoretical foundations like complexity analysis of algorithms. Examples are provided in pseudocode, which can easily be translated to any programming language, including Python.
It will be useful for Computer Science students, grad students, and professional developers.
I wanted to recommend it before the algorithms course started, but decided to hold off until the end — don't wanna scare some of you off. The book has 1000 pages and weighs about two kilograms.
10.2 Grokking Algorithms
Book number two is “Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People” by Aditya Bhargava. It looks like this:
The book is presented in a visual and accessible way, making it ideal for beginners. There are plenty of illustrations to explain how algorithms work. Each section reviews different algorithms, starting from basic concepts and moving to more complex topics.
Examples are written in Python, allowing readers to immediately apply the knowledge in practice. It's useful for budding developers, students, and anyone who wants to quickly get the hang of algorithm basics.
10.3 Data Structures and Algorithms in Python
What else to read? “Data Structures and Algorithms in Python”. Originally called "Data Structures and Algorithms in Python" by Michael T. Goodrich.
This book is an adaptation of a popular textbook on data structures and algorithms for the Python language.
It covers basic and complex data structures and algorithms, such as arrays, lists, stacks, queues, trees, graphs, and hash tables. It also discusses sorting, searching algorithms, and many others.
Examples and code are written in Python, making it handy for developers working with this language. Intended audience: students, beginner developers, and anyone who wants to explore data structures and algorithms using Python.
10.4 Algorithms in a Nutshell
Not enough for you? Then I've got “Algorithms in a Nutshell” for you.
The book provides a concise and practical guide to algorithms. Includes descriptions and implementations of various algorithms, such as sorting, searching, graph algorithms, and others. The book focuses on practical applications of algorithms.
Implementation examples are provided in Python and other programming languages. It's of interest to professional developers and engineers who want to quickly find and use algorithms to solve their tasks.
10.5 Algorithms in Python
How about a bit of “crushing” you with inspiration? Oops, I meant “inspire” :)
"Algorithms in Python: mastering the essential algorithms in Python"
This book focuses on implementing and using essential algorithms in Python. It covers sorting, searching, trees, graphs, and many other algorithms. Python code examples and step-by-step explanations make it an ideal choice for those looking to deepen their knowledge.
Suitable for Python developers with basic knowledge, eager to master algorithms in practice.
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