50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography

Price: $49.99 – $28.50
(as of Dec 24,2024 03:43:53 UTC – Details)

From the Publisher

What makes this book different from other books on algorithms for programmers?

While many algorithm books cover traditional and foundational topics, I’ve tried to keep this book modern by diving into state-of-the-art algorithms in areas like deep learning, Large Language Models (LLMs), and sequential models. I want to show that the world of algorithms, is not static, but always evolving, which I also think is a more comprehensive view of algorithms.

An important topic I’d want to bring up about this is bias and explainability. In today’s world, where AI ethics is crucial, I’ve wanted this book to stand out in addressing the all-important topic of recognizing hidden biases in data and ensuring the transparency and explainability of algorithms.

(Image: Deep and wide LLM architecture models)

What this book covers

Neural networks and deep learning
Graph algorithms for fraud detection
Machine learning applications
Natural language processing
Large Language Models
Recommendation systems
Cryptography on cloud platforms
Parallel processing techniques

This second edition of 50 Algorithms Every Programmer Should Know not only has the updated versions of most algorithms from the first edition in line with current IT trends, but it also aims to help readers delve into advanced deep learning architectures and new chapters on sequential models like LSTMs, GRUs, RNNs, and LLMs.

Furthermore, through this edition, I’ve tried to shed light on contemporary topics such as addressing hidden data biases and demystifying algorithm explainability.

What approach does this book take to get readers started?

I’ve designed this book to strike a balance between helping readers select and use an algorithm to solve a real-world problem and explaining the logic behind it for a deeper understanding.

For example, it begins with an introduction to algorithms, allowing readers to understand the various algorithm design techniques. As readers progress, they explore more advanced concepts and are taught the practical application of these algorithms using real-world examples.

(Image: A fundamental algorithm design)

How has your career helped you write this book?

I’ve had a rich background in cloud computing, AI, and machine learning that I want to bring to the table with this book. I’ve had experience in high-profile projects with the Canadian Federal Government, taught at Google, and am a visiting professor at Carleton University. My experience in all of these different projects with their own focuses and challenges has taught me some insights that I’d like to share, whether it’s about the applicability of some algorithms, or maybe their ethics, or their future direction. I hope it also adds a unique perspective to what I’ve written.

Publisher ‏ : ‎ Packt Publishing; 2nd ed. edition (September 27, 2023)
Language ‏ : ‎ English
Paperback ‏ : ‎ 538 pages
ISBN-10 ‏ : ‎ 1803247762
ISBN-13 ‏ : ‎ 978-1803247762
Item Weight ‏ : ‎ 2.05 pounds
Dimensions ‏ : ‎ 1.21 x 7.5 x 9.25 inches

Algorithms are the building blocks of computer science, powering everything from search engines to social media platforms. As a programmer, having a strong foundation in algorithms is crucial for tackling complex problems and optimizing code performance. In this post, we’ll explore 50 essential algorithms that every programmer should know, spanning a range of topics including machine learning, software design, data systems, and cryptography.

1. Binary search
2. Bubble sort
3. Merge sort
4. Quick sort
5. Dijkstra’s algorithm
6. A* search algorithm
7. Bellman-Ford algorithm
8. Floyd-Warshall algorithm
9. Prim’s algorithm
10. Kruskal’s algorithm
11. Depth-first search (DFS)
12. Breadth-first search (BFS)
13. Dynamic programming
14. Greedy algorithms
15. K-nearest neighbors (KNN)
16. Support vector machines (SVM)
17. Decision trees
18. Random forests
19. K-means clustering
20. Principal component analysis (PCA)
21. Apriori algorithm
22. PageRank algorithm
23. MapReduce
24. Bloom filter
25. Rabin-Karp algorithm
26. RSA encryption
27. Diffie-Hellman key exchange
28. AES encryption
29. SHA-256 hashing
30. MD5 hashing
31. B-tree
32. Red-black tree
33. AVL tree
34. Trie
35. Skip list
36. Hash table
37. Graph representation (adjacency matrix, adjacency list)
38. Topological sorting
39. Bellman-Ford algorithm
40. Floyd-Warshall algorithm
41. Prim’s algorithm
42. Kruskal’s algorithm
43. Ford-Fulkerson algorithm
44. Edmonds-Karp algorithm
45. Hungarian algorithm
46. Fast Fourier Transform (FFT)
47. Strassen’s algorithm
48. Knuth-Morris-Pratt algorithm
49. Boyer-Moore algorithm
50. Levenshtein distance

By mastering these algorithms, you’ll be well-equipped to tackle a wide range of computer science challenges, from optimizing search algorithms to designing secure cryptographic systems. Whether you’re a beginner or a seasoned programmer, learning and understanding these algorithms will help you become a more efficient and effective coder. So dive in, explore these algorithms, and level up your programming skills today!
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