Enabling AI Applications in Data Science

by Aboul-Ella Hassanien (Editor), Mohamed Hamed N. Taha (Editor), Nour Eldeen M. Khalifa (Editor)

Overview

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.

Product Details

ISBN-13:	9783030520694
Publisher:	Springer International Publishing
Publication date:	09/23/2020
Series:	Studies in Computational Intelligence , #911
Edition description:	1st ed. 2021
Pages:	650
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Part I: Artificial Intelligence and Optimization.- Shastic 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.