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40 Algorithms Every Programmer Should Know

You're reading from   40 Algorithms Every Programmer Should Know Hone your problem-solving skills by learning different algorithms and their implementation in Python

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781789801217
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Imran Ahmad Imran Ahmad
Author Profile Icon Imran Ahmad
Imran Ahmad
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Fundamentals and Core Algorithms
2. Overview of Algorithms FREE CHAPTER 3. Data Structures Used in Algorithms 4. Sorting and Searching Algorithms 5. Designing Algorithms 6. Graph Algorithms 7. Section 2: Machine Learning Algorithms
8. Unsupervised Machine Learning Algorithms 9. Traditional Supervised Learning Algorithms 10. Neural Network Algorithms 11. Algorithms for Natural Language Processing 12. Recommendation Engines 13. Section 3: Advanced Topics
14. Data Algorithms 15. Cryptography 16. Large-Scale Algorithms 17. Practical Considerations 18. Other Books You May Enjoy

Practical application – solving the TSP

Let's first look at the problem statement for the TSP, which is a well-known problem that was coined as a challenge in the 1930s. The TSP is an NP-hard problem. To start with, we can randomly generate a tour that meets the condition of visiting all of the cities without caring about the optimal solution. Then, we can work to improve the solution with each iteration. Each tour generated in an iteration is called a candidate solution (also called a certificate). Proving that a certificate is optimal requires an exponentially increasing amount of time. Instead, different heuristics-based solutions are used that generate tours that are near to optimal but are not optimal.

A traveling salesman needs to visit a given list of cities to get their job done:

INPUT A list of n cities (denoted as V) and the distances between each pair...
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