by Aditya Y. Bhargava | Released May 2016 | ISBN: None

"This book does the impossible: it makes math fun and easy!" Sander Rossel, COAS Software Systems Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this video editions course, you will have mastered widely applicable algorithms as well as how and when to use them. An algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to understand them but refuse to slog through dense multipage proofs, you are at the right place. This fully illustrated and engaging guide makes it easy to learn how to use the most important algorithms effectively in your own programs. Inside: Covers search, sort, and graph algorithms Over 400 pictures with detailed walkthroughs Performance trade-offs between algorithms Python-based code samples This easy-to-read, picture-heavy introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Aditya Bhargava is a Software Engineer with a dual background in Computer Science and Fine Arts. He blogs on programming at adit.io. Do you want to treat yourself to learning algorithms in the same way that you would read your favorite novel? If so, this is the book you need! Sankar Ramanathan, IBM Analytics In today's world, there is no aspect of our lives that isn't optimized by some algorithm. Let this be the first book you pick up if you want a well-explained introduction to the topic. Amit Lamba, Tech Overture, LLC Algorithms are not boring! This book was fun and insightful for both my students and me. Christopher Haupt, Mobirobo, Inc NARRATED BY DEREK LETTMAN Show and hide more

1. Chapter 1. Introduction to Algorithms 00:05:45
2. Chapter 1. A Better Way to Search 00:06:10
3. Chapter 1. Algorithm running times grow at different rates 00:07:41
4. Chapter 1. Some common Big O run times 00:05:50
5. Chapter 2. Selection Sort 00:08:46
6. Chapter 2. Terminology 00:08:09
7. Chapter 3. Recursion 00:04:54
8. Chapter 3. The Stack 00:06:41
9. Chapter 4. Quicksort - 1st part 00:08:32
10. Chapter 4. Quicksort - 2nd part 00:06:02
11. Chapter 4. Big O notation revisited 00:07:34
12. Chapter 5. Hash Tables 00:07:37
13. Chapter 5. Use Cases 00:08:20
14. Chapter 5. Collisions 00:03:41
15. Chapter 5. Performance 00:06:48
16. Chapter 6. Breadth-first Search 00:06:22
17. Chapter 6. Finding the shortest path 00:03:31
18. Chapter 6. Implementing the graph 00:06:57
19. Chapter 7. Dijkstra’s algorithm 00:07:20
20. Chapter 7. Trading for a piano 00:06:08
21. Chapter 7. Negative-weight edges 00:08:09
22. Chapter 8. Greedy Algorithms 00:06:33
23. Chapter 8. Approximation algorithms 00:05:19
24. Chapter 8. NP-complete problems 00:09:09
25. Chapter 9. Dynamic Programming - 1st part 00:05:26
26. Chapter 9. Dynamic programming - 2nd part 00:07:52
27. Chapter 9. Can you steal fractions of an item? 00:04:18
28. Chapter 9. Longest common substring 00:09:05
29. Chapter 10. K-nearest neighbors 00:06:10
30. Chapter 10. Regression 00:05:22
31. Chapter 10. OCR 00:04:20
32. Chapter 11. Where to go next 00:07:10
33. Chapter 11. MapReduce 00:07:38
34. Chapter 11. The SHA algorithms 00:04:58
35. Chapter 11. Diffie-Hellman key exchange 00:05:09
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