English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 4h 40m | 529 MB
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.
Learning about algorithms doesn’t have to be boring! Get a sneak peek at the fun, illustrated, and friendly examples you’ll find in Grokking Algorithms on YouTube.
If you want to get more from the classic algorithms inside this book then be sure to check out Algorithms in Motion. Together this book and video course make the perfect duo.
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, this is the book for you. This fully illustrated and engaging guide makes it easy to learn how to use the most important algorithms effectively in your own programs.
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 book, you will have mastered widely applicable algorithms as well as how and when to use them.
What’s inside
- Covers search, sort, and graph algorithms
- Over 400 pictures with detailed walkthroughs
- Performance trade-offs between algorithms
- Python-based code samples
Table of Contents
1 Introduction_to_algorithms
2 Selection_sort
3 Recursion
4 Quicksort
5 Hash_tables
6 Breadth-first_search
7 Trees
8 Balanced_trees
9 Dijkstra_s_algorithm
10 Greedy_algorithms
11 Dynamic_programming
12 k-nearest_neighbors
13 Where_to_go_next
14 Performance_of_AVL_trees
15 NP-hard_problems
16 Answers_to_exercises
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