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portada Enabling AI Applications in Data Science
Type
Physical Book
Publisher
Author
Language
English
Pages
650
Format
Paperback
Dimensions
23.4 x 15.6 x 3.4 cm
Weight
0.91 kg.
ISBN13
9783030520694
Categories

Enabling AI Applications in Data Science

Hassanien, Aboul-Ella ; Taha, Mohamed Hamed N. ; Khalifa, Nour Eldeen M. (Author) · Springer · Paperback

Enabling AI Applications in Data Science - Hassanien, Aboul-Ella ; Taha, Mohamed Hamed N. ; Khalifa, Nour Eldeen M.

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Synopsis "Enabling AI Applications in Data Science"

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.

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