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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 started by looking at the basics of supervised machine learning. Then, we looked at various classification algorithms in more detail. Next, we looked at different methods to evaluate the performance of classifiers and studied various regression algorithms. We also looked at the different methods that can be used to evaluate the performance of the algorithms that we studied.In the next chapter, we will look at neural networks and deep learning algorithms. We will look at the methods used to train a neural network and we will also look at the various tools and frameworks available for evaluating and deploying a neural network.

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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