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Enabling AI applications in data science / Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa, editors.

Hassanien, Aboul Ella, editor.
2021
Q335 .E53 2021
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Title
Enabling AI applications in data science / Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa, editors.
ISBN
9783030520670 (electronic book)
3030520676 (electronic book)
3030520668
9783030520663
Published
Cham, Switzerland : Springer, [2021]
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-030-52
Call Number
Q335 .E53 2021
Dewey Decimal Classification
006.3
Summary
This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from digital title page (viewed on October 22, 2020).
Added Author
Hassanien, Aboul Ella, editor.
Series
Studies in computational intelligence ; v. 911.
Available in Other Form
Enabling AI applications in data science.
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All Resources
Part I: Artificial Intelligence and Optimization
Stochastic Proximal Gradient Algorithm with Minibatches Application to Large Scale Learning Models
The Human Mental Search Algorithm for Solving Optimisation Problems
Reducing Redundant Association Rules Using Type-2 Fuzzy Logic
Identiability of Discrete Concentration Graphical Models with a Latent Variable
An Automatic Classication of Genetic Mutations by Exploring Different Classiers
Towards Artificial Intelligence: Concepts, Applications, and Innovations
Part II: Big Data and Artificial Intelligence Applications
In Depth Analysis, Applications and Future Issues of Articial Neural Network
Big Data and Deep Learning in Plant Leaf Diseases Classification for Agriculture
Machine Learning Cancer Diagnosis Based on Medical Image Size and Modalities.

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