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ERPSummer School On Research In Artificial Intelligence And Deep Learning
Summer School On Research In Artificial Intelligence And Deep Learning
Summer School On Research In Artificial Intelligence And Deep Learning
A 5-day summer school on “Research in Artificial Intelligence and Deep Learning” in association with CSI and NVIDIA was conducted by Department of Computer Science and Engineering and Machine Intelligence and Data Analytics Research Centre (MIDARC) from 11 to 15 June 2019. Around 40 participants were benefitted from the school. Dr. M.G. Sumithra, Group Head, Artificial Intelligence Real Time Application Group (AIRAG) and Mr. V. Chandran, Trainer, AIRAG were the Chief Guest and Guest of Honour.
In her address, Dr. Sumithra introduced deep learning and convolution neural networks; and gave hands on sessions on handwriting recognition and image segmentation using MATLAB. Ms. M. Suriya, Trainer, AIRAG explained about Deep Learning for Natural Language Processing; and was involved in hands on session on spam detection using Anaconda and text classification using RNN and CNN. Mr. V. Chandran elaborated on the fundamentals of Deep Learning for computer vision, and hands on session in NVIDIA GPU Task 1 to 5 followed by assessment. 20 participants completed the NVIDIA certification on “Fundamentals of Deep Learning for Computer Vision” from NVIDIA Deep Learning Institute. Mr. V. Chandran and Ms. M. Suriya were also involved in hands on training about image generation using generative adversarial networks and time series analysis using Keras.
Whilst Dr. Angelina Geetha, Professor, HITS detailed the concept of Drift, Dr P. S. Sreeja, Associate Professor, HITS analyzed a case study on Emotion Recognition using Poems; and Dr. Judith Leo, Assistant Professor, HITS gave a demonstration using IBM Minsky server and use of GPU server with live examples.
Topics
- Deep Learning for Natural Language Processing Artificial Intelligence
- Deep Learning for Digital Content Creation
- Deep Learning for Computer Vision
- TensorFlow, MXNet, and NVIDIA Docker
- Modeling Time Series Data with Recurrent Neural Networks in Keras
