An algorithm is a step-by-step method for solving programming problems.
Actually, it’s kind of like a recipe: a combination of ingredients to come up with a delicious finished product...And having the best resources is the key to success.
Today we’re showing you 11 of the best algorithms books for 2021.
In addition, we’re pairing some of them with killer courses for the ultimate algorithm prep combo.
This post contains affiliate links. I may receive compensation if you buy something. Read my disclosure for more details.
Our top picks for the best algorithms books in 2021:
Data Structures & Algorithms in Python is a comprehensive introduction to algorithms presented in the programming language Python.
Here you’ll learn about the design, analysis and implementation of algorithms.
First off, you’ll start with a Python primer.
Then, you’ll learn about:
- object-oriented programming
- algorithm analysis
- sorting and selection
- graph algorithms
- array-based sequences
And much more.
You must be familiar with C, C++, Python or Java before reading this book.
PAIRING SUGGESTION We recommend pairing this book with the Educative.io course Data Structures and Algorithms in Python. This is an intermediate interactive course. Also, it’s jam-packed with illustrations, code snippets and code playgrounds.
In addition, you’ll learn some of the most common algorithms in use today. With hands-on coding exercises, you’ll learn how to implement algorithms to solve most problems.
Read more about Data Structures & Algorithms in Python
As the name suggests, The Algorithms Design Manual stresses design over analysis.
The first part of this textbook covers methods to design and analyze computer algorithms.
Then the second part is a reference guide for algorithmic resources and implementations.
In addition, it’s jam-packed with color illustrations and code.
You’ll learn the best algorithmic implementations in C, C++, and Java.
Read more about The Algorithm Design Manual
This book is amazing. It is rigorous yet approachable for anyone who likes a challenge. Definitely a keeper.
Introduction to Algorithms is an in-depth look at different algorithm types. However, explanations are elementary.
Therefore, the material is still accessible for beginner and intermediate learners.
In addition, each chapter is self-contained so there’s no bleed-through of information.
Algorithms are presented in pseudocode for widespread readability.
This updated version of Introduction to Algorithms includes new material such as multithreaded algorithms and dynamic programming.
This textbook has been used in universities worldwide.
Read more about Introduction to Algorithms, 3rd Edition
Algorithms is another textbook used in universities worldwide.
It includes 50 of the most commonly used and up-to-date algorithms.
Algorithm types include:
- graph processing
- string processing
Algorithms and solutions are written in Java.
With the online courses, you’ll:
- work on exercises
- look at lecture slides
- work on programming assignments
Read more about Algorithms (4th Edition)
Mastering Machine Learning Algorithms is geared towards data science professionals.
In addition to learning the characteristics of machine learning algorithms, you’ll learn:
- implement algorithms for supervised, unsupervised and reinforcement learning
- discover how artificial neuron networks work
- create, model and train probabilistic models
- learn how regression works
And much, much more.
Solutions are presented in Python 3.8, so you must be familiar with Python.
PAIRING SUGGESTION : If you’re looking to work on even more complex algorithms, we recommend the AlgoExpert platform by Clément Mihailescu.
Then, you can work on over 100 problems ranging from Easy to Extremely Hard. AlgoExpert is geared towards preparing for FAANG interviews, but can also be used just to keep your algorithmic skills sharp.
Read more about Mastering Machine Learning Algorithms
Simply on of the best books on algorithms you will ever find. Period.
C. L. Beard
Algorithms in a Nutshell takes a hands-on approach to applying algorithms with minimal use of math.
In addition, each algorithm contains an explanation for where, why and how it should be implemented.
You’ll also learn how to:
- use design decisions to impact different algorithms
- locate algorithms for the problems you want to solve
- anticipate the performance of an algorithm
- improve the efficiency of algorithms with data structures
Code solutions are presented in C, C++, Java and Python.
Read more about Algorithms in a Nutshell
A Common Sense Guide to Data Structures takes a real-world, practical approach to teaching algorithms.
For example, you’ll use big-O notation to measures the efficiency of your code.
Also, from there you can modify your algorithm to make it faster.
In addition, you’ll use recursion to create algorithms to run faster.
Finally you’ll work on advanced data structures to scale specialized applications.
Read more about A Common-Sense Guide to Data Structures and Algorithms
Grokking Algorithms is a user-friendly book geared towards self-taught programmers.
In addition, the easy-to-read format contains over 400 illustrations.
After a brief introduction, you’ll learn nine of the most important and frequently-used algorithms:
- Selection sort
- Hash tables
- Breadth-first search
- Dijkstra’s algorithm
- Greedy algorithms
- Dynamic programming
- K-nearest neighbors
These are all algorithms related to search, sort and graph.
Code samples are given in Python.
At the conclusion of Grokking Algorithms , you’ll know when and where to use common algorithms.
PAIRING SUGGESTION : This book pairs well with Andrei Neagoie’s video course Master the Coding Interview: Data Structures + Algorithms. Both are great for beginners.
In addition to 19 hours of videos, Master the Coding Interview will teach you how to learn, implement and use different data structures and algorithms.
In addition, you’ll learn how to prepare for FAANG-level interviews.
Read more about Grokking Algorithms
Like the titles says, you’ll learn how to implement data structures and algorithms using Python.
Specifically, you’ll learn some of the most common algorithms to build manageable applications.
You’ll also use algorithms to understand data structures.
In addition, you’ll be learn how to gain insights into Python implementation of algorithms.
And much more.
As a result, you’ll be able to write efficient code in Python 3.
You should be familiar with Python before reading this book.
PAIRING SUGGESTION : If you need to learn Python, Codecademy offers an excellent Python beginners course Learn Python 3. Then dive into this book.
Read more about Hands-On Data Structures and Algorithms with Python
40 Algorithms Every Programmer Should Know is geared towards both beginner and experienced programmers.
If you’re hoping to land a FAANG-level job, this book needs to be on your bookshelf.
You’ll learn fundamental algorithms such as sorting and searching. In addition, you’ll learn algorithms commonly used in machine learning and cryptography.
Using Python, you’ll learn how to:
- implement graph algorithms for fraud detection
- use machine learning algorithms to process Twitter data
- use supervised learning algorithms to predict weather
And much more.
In addition, you’ll learn techniques to design algorithms which solve complex problems.
Also, you’ll become familiar with neural networks and deep learning.
Read more about 40 Algorithms Every Programmer Should Know
Algorithms Illuminated is a 4-part series. Part 1 deals with algorithm basics.
Here you’ll learn a programming language-agnostic approach to algorithms.
In other words, the code examples aren’t presented in a specific programming language.
Rather, you’ll learn the skills you need to create algorithms in various languages.
Also, Algorithms Illuminated includes quizzes, problems and solutions.
Author Tim Roughgarden presents concepts with accompanying YouTube videos.
Then, Algorithms Illuminated: Part 1 will cover things like divide-and-conquer algorithms, randomized algorithms, and widely-known sorting and selection algorithms.
And much more.
Read more about Algorithms Illuminated: Part 1: The Basics
Be sure to check out the other books in this series.
Best Algorithms Books Bonus: The Cambridge Handbook of the Law of Algorithms
The Cambridge Handbook of the Law of Algorithms examines our legal and ethical responsibility to use algorithms.
Then, it examines challenges algorithms pose to law.
For example, algorithms are often used to determine things like prison sentences.
In addition, it looks at how algorithms are replacing people as decision makers.
But with that, it analyzes how human biases are built into algorithmic decision making. Some instances include housing, credit approval and more.
Finally, it takes a look at algorithms in relation to free speech, intellectual property and human rights.
Today we showed you 11 of the best algorithms books available:
- Data Structures & Algorithms in Python
- The Algorithm Design Manual
- Introduction to Algorithms, 3rd Edition (The MIT Press)
- Algorithms (4th Edition)
- Mastering Machine Learning Algorithms
- Algorithms in a Nutshell
- A Common-Sense Guide to Data Structures and Algorithms, Second Edition
- Grokking Algorithms
- Hands-On Data Structures and Algorithms with Python
- 40 Algorithms Every Programmer Should Know
- Algorithms Illuminated: Part 1: The Basics
In addition, we included the bonus book The Cambridge Handbook of the Law of Algorithms.
Finally, we included some courses to complement some of the books.
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