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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
Concepts
Data Structures and Algorithms
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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 journeyed through the evolution of neural networks, examining different types, key components like activation functions, and the significant gradient descent algorithm. We touched upon the concept of transfer learning and its practical application in identifying fraudulent documents.

As we proceed to the next chapter, we’ll delve into natural language processing, exploring areas such as word embedding and recurrent networks. We will also learn how to implement sentiment analysis. The captivating realm of neural networks continues to unfold.

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50 Algorithms Every Programmer Should Know - Second Edition
Published in: Sep 2023Publisher: PacktISBN-13: 9781803247762
© 2023 Packt Publishing Limited All Rights Reserved

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

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