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40 Algorithms Every Programmer Should Know

You're reading from 40 Algorithms Every Programmer Should Know

Product type Book

Published in Jun 2020

Publisher Packt

ISBN-13 9781789801217

Pages 382 pages

Edition 1st Edition

Languages

Concepts

Data Structures and Algorithms

Author (1):

Imran Ahmad

Table of Contents (19) Chapters

Preface

1. Section 1: Fundamentals and Core Algorithms

2. Overview of Algorithms

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

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Who this book is for

This book is for the serious programmer! Whether you are an experienced programmer looking to gain a deeper understanding of the math behind the algorithms or have limited programming or data science knowledge and want to learn more about how you can take advantage of these battle-tested algorithms to improve the way you design and write code, you’ll find this book useful. Experience with Python programming is a must, although knowledge of data science is helpful but not necessary.

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Authors (1)

Imran Ahmad

Imran Ahmad has been a part of cutting-edge research about algorithms and machine learning for many years. He completed his PhD in 2010, in which he proposed a new linear programming-based algorithm that can be used to optimally assign resources in a large-scale cloud computing environment. In 2017, Imran developed a real-time analytics framework named StreamSensing. He has since authored multiple research papers that use StreamSensing to process multimedia data for various machine learning algorithms. Imran is currently working at Advanced Analytics Solution Center (A2SC) at the Canadian Federal Government as a data scientist. He is using machine learning algorithms for critical use cases. Imran is a visiting professor at Carleton University, Ottawa. He has also been teaching for Google and Learning Tree for the last few years.

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