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You're reading from  50 Algorithms Every Programmer Should Know - Second Edition

Product typeBook
Published inSep 2023
PublisherPackt
ISBN-139781803247762
Edition2nd Edition
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Author (1)
Imran Ahmad
Imran Ahmad
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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.
Read more about Imran Ahmad

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Summary

In this chapter, we learned about the practical aspects that should be considered while designing algorithms. We looked into the concept of algorithmic explainability and the various ways we can provide it at different levels. We also looked into the potential ethical issues in algorithms. Finally, we described which factors to consider while choosing an algorithm.

Algorithms are engines in the new automated world that we are witnessing today. It is important to learn about, experiment with, and understand the implications of using algorithms. Understanding their strengths and limitations and the ethical implications of using algorithms will go a long way in making this world a better place to live in, and this book is an effort to achieve this important goal in this ever-changing and evolving world.

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50 Algorithms Every Programmer Should Know - Second Edition
Published in: Sep 2023Publisher: PacktISBN-13: 9781803247762

Author (1)

author image
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.
Read more about Imran Ahmad