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Annals of Data Science
Published in:

28-03-2022

“Transfer Learning” for Bridging the Gap Between Data Sciences and the Deep Learning

Author: Ayesha Sohail

Published in: Annals of Data Science | Issue 1/2024

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Abstract

Over the past two decades, the community of data science, computer vision and programming has evolved rapidly and new programming techniques have replaced the computationally expensive techniques. This is achieved with the aid of smart programming languages, smart computers and intelligent minds. The neural networks are replaced by the deep neural networks which are comprised of several layers and neurons, the direct large data “classification” has been replaced by the transfer learning tools, which are computationally more efficient and accurate as long as the user has the clear vision of synchronizing the new problem with the pre-trained model. Artificial intelligence tools are much improved since the discovery of transfer learning tools and the programming time of several days or weeks for the deep networks has now reduced to few minutes or hours. This article presents detailed insight of transfer learning frame work with the aid of some useful programming tools.
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Metadata
Title
“Transfer Learning” for Bridging the Gap Between Data Sciences and the Deep Learning
Author
Ayesha Sohail
Publication date
28-03-2022
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 1/2024
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-022-00384-x

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Context-Based Bigram Model for POS Tagging in Hindi: A Heuristic Approach

A Comprehensive Study of Artificial Intelligence and Cybersecurity on Bitcoin, Crypto Currency and Banking System

A Review on Applications of Chaotic Maps in Pseudo-Random Number Generators and Encryption

On Poisson Moment Exponential Distribution with Applications

Deep Neural Network (DNN) Mechanism for Identification of Diseased and Healthy Plant Leaf Images Using Computer Vision

Modeling the Impact of Delay on the Aggregation of AD Proteins

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