Buch, Englisch, 256 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 540 g
A Hands-on Approach
Buch, Englisch, 256 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 540 g
Reihe: Chapman & Hall/CRC Cloud Computing for Society 5.0
ISBN: 978-1-032-10567-3
Verlag: Taylor & Francis Ltd (Sales)
Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solution using cloud. It includes the fundamentals of neural networks, different types and how they can be used for the multi-modal information analytics. The various application areas that are image-centric and videos are also presented with deployment solutions in the cloud.
Features
- Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video.
- Deep Learning fundamentals and architectures covering convolutional Neural Networks, recurrremt neural networks, and types of learning for different multi-modal networks.
- Applications of Multi-Modal Analytics covering Text, Speech, and Image.
This book is aimed at researchers in Multi-modal analytics and related areas
Zielgruppe
Academic, Postgraduate, Professional, Undergraduate Advanced, and Undergraduate Core
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik Mathematik Mathematik Allgemein
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
- Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
Weitere Infos & Material
Part 1: Introduction to Cloud based Multi-Modal data and Analytics
1. Multi-Modal data analytics and lifecycle using Cloud. 2. Cloud Computing. 3. Overview of Deep learning. 4. Deep Learning Platforms and Cloud
Part 2: Architectures & Examples for Multi-Modal data and Analytics using Cloud
5. Neural Networks for Multi-modal data analytics. 6. Cloud examples for Neural Networks Multi-modal architectures. 7. Training Neural Networks on Cloud
Part 3: Cloud based Applications of Multi-Modal Analytics
8. Image Analytics. 9. Text Analytics. 10. Speech Analytics. Exercises.