The Workshop on Deep Learning and its Applications is the first workshop as a sister concern event of 18th ICDCIT 2022 . This workshop covers the concepts of deep learning algorithms and their applications in various domains. The training comprises a series of lectures, research work presentations, and practical hands-on sessions. The participants will obtain in-depth insights into deep learning, which in turn will help them to apply it in practice and also will work as a foundation to an extensive study in this area.
Introduction to Deep Learning
Deep Learning Process
Deep Learning techniques and case studies
Deep Learning Tools/Frameworks
Hands-on experience in Deep Learning Applications
Key Resource Persons
Prof. (Dr.) Dipti Prasad Mukherjee
Deputy Director and Professor (HAG)
Electronics and Communication Sciences Unit, CCSD, Indian Statistical Institute, Kolkata
Dr. Bikash Santra
Visiting Scientist, Electronics and Communication Sciences Unit,Indian Statistical Institute, Kolkata
Mrs. Maneesha Nanda
V.P. Wells Fargo Enterprise Solution Architect with the specialization in Data Engineering and Application Modernization, IIT Delhi Alumni
Dr. Rituparna Sarkar
Scientific Researcher, Institute Pasteur, Paris
Research interests are in the area of image analysis, machine learning, and bioimage informatics.
Mr. Saikat Sarkar
Dept. of Computer Science, Bangabasi College, University of Calcutta
UG/PG/Ph.D Scholars and faculties interested to learn the concepts of Deep Learning and its applications.
Note: The workshop has limited seats. The participants will be registered based on first come first serve.
Basic experience in programming using Python will help do practical exercises. We assume no prior knowledge in machine learning/deep learning, however, basic knowledge of statistics will be helpful.
Registration fees for Indian participants (outside KIIT DU.): 400.00 INR
Registration fees for International participants (outside KIIT DU.): 50 USD
Registration fees for KIIT DU. participants: 200.00 INR
Registration starts from 5th December 2021 Registration closes by 15th January 2022