The text discusses various modalities of data and provides aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. Various image-centric and video application areas are presented with deployment solutions in the cloud.

Dr. Srinidhi Hiriyannaiah is working as senior software engineering in GE Healthcare, he received his Ph.D. degree from VTU during 2020 and did his Master of Technology in Software Engineering from M.S. Ramaiah Institute of Technology, Bengaluru (VTU). He worked as Assistant Professor in Department of Computer Science and Engineering at M.S. Ramaiah Institute of Technology, Bengaluru from 2016-2022. He previously worked at IBM India Software Labs, Bengaluru. His main area of interest includes studies related to parallel computing, big data and its applications, information management and software engineering for education.

Dr. Siddesh G M is currently working as professor in Department of Computer Science & Engineering (Cyber Security), M S Ramaiah Institute of Technology, Bangalore. He has published a good number of research papers in reputed International Conferences and Journals. He is a member of ISTE, IETE etc., He has authored books on Network Data Analytics, Statistical Programming in R, Internet of Things with Springer, Oxford University Press and Cengage publishers respectively. He has edited research monographs in the area of Cyber Physical Systems, Fog Computing and Energy Aware Computing, Bioinformatics with CRC Press, IGI Global and Springer publishers respectively. His research interests include Internet of Things, Distributed Computing and Data Analytics.

Dr. Srinivasa K G is a Professor of Data Science and Artificial Intelligence Programme at DSPM IIIT-Naya Raipur, C. G. India. Earlier he worked as a Professor at Information Management and Emerging Engineering Department of National Institute of Technical Teachers Training and Research, Chandigarh an autonomous Institute under Ministry of Education, Government of India. He also worked as an Associate Professor at CBP Government Engineering College, New Delhi (through UPSC) between 2016 - 19. He also served as Professor in the Department of CSE at M S Ramaiah Institute of Technology, Bangalore between 2003 - 2016.
He received his Ph.D. in Computer Science and Engineering from Bangalore University in 2007. He is the recipient of All India Council for Technical Education - Career Award for Young Teachers, Indian Society of Technical Education - ISGITS National Award for Best Research Work Done by Young Teachers, Institution of Engineers (India) - IEI Young Engineer Award in Computer Engineering, Rajarambapu Patil National Award for Promising Engineering Teacher Award from ISTE - 2012, IMS Singapore - Visiting Scientist Fellowship Award. He has published more than 150 research papers in International Conferences and Journals. He has visited many Universities abroad as a visiting researcher - He has visited University of Oklahoma, USA, Iowa State University, USA, Hong Kong University, Korean University, National University of Singapore, University of British Columbia, Canada are his few prominent visits. He has authored many books in the area of Learning Analytics, Network Data Analytics, Soft Computing, Social Network Analysis, High Performance Computing, R Programming etc. with prestigious international publishers like Springer, TMH, Oxford, Cengage, and IGI Global. He has edited research monographs in the area of Cyber Physical Systems, Fog Computing and Energy Aware Computing with CRC Press and IGI Global.
He has been awarded BOYSCAST Fellowship by DST, Govt. of India, for conducting post-doctoral research work at University of Melbourne, Australia. He is the principal Investigator for many funded projects from AICTE, UGC, DRDO, and DST. He has undertaken consultancy projects worth 60 lakhs towards conducting Professional Development Programmes under World Bank Project. He is the senior member of IEEE and ACM. His recent research areas include Innovative Teaching Practices in Engineering Education, pedagogy; outcomes based education, and teaching philosophy.

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.