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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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Index

A

abstract data types (ADT)

exploring 43

queues 47, 49

stacks 45-47

tree 50

vector 43, 44

abstract data types (ADT), stacks

practical example 47

time complexity 47

abstract data types (ADT), vector

time complexity 44

actionable rules

examples 176

activation functions 262

hyperbolic tangent (tanh) function 268, 269

ReLU activation function 266

sigmoid function 264, 265

softmax function 269, 270

step function 264

adjacency list

constructing 126

Advanced Encryption Standard (AES) 424

advanced lossless compression formats 404

GZIP compression 405

LZO compression 404

snappy compression 404

advanced sequential modeling techniques

evolution 346, 347

AI spring 252

AI winter 252

algorithm 4, 9

approximate algorithm 23

coding phase 6

compute-intensive algorithms 10

data-intensive algorithms 10

design phase 5

deterministic algorithm 22

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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