Enabling AI applications in data science
- Responsibility
- Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa, editors.
- Publication
- Cham, Switzerland : Springer, [2021]
- Physical description
- 1 online resource
- Series
- Studies in computational intelligence ; v. 911.
Online
Available online
More options
Description
Creators/Contributors
- Contributor
- Hassanien, Aboul Ella, editor.
Contents/Summary
- Bibliography
- Includes bibliographical references.
- Contents
-
- 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.- Identifiability of Discrete Concentration Graphical Models with a Latent Variable.- An Automatic Classification of Genetic Mutations by Exploring Different Classifiers.- Towards Artificial Intelligence: Concepts, Applications, and Innovations.- Part II: Big Data and Artificial Intelligence Applications.- In Depth Analysis, Applications and Future Issues of Artificial 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.
- (source: Nielsen Book Data)
- Publisher's 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.
(source: Nielsen Book Data)
Subjects
Bibliographic information
- Publication date
- 2021
- Series
- Studies in computational intelligence ; volume 911
- ISBN
- 9783030520670 (electronic book)
- 3030520676 (electronic book)
- 3030520668
- 9783030520663
Browse related items
Start at call number:
