Deep Learning and Its Applications (NKN Winter Course) @ E & ICT Academy, NIT Warangal

Participants Information

Participants:	16
Speakers:	06
Female participants:	06
Male participants:	10
Participants from SC/ST category:	02
Research Scholars:	03

Lab Sessions

• Practice session on Python Programming
• Introduction to TensorFlow, Keras, program on ANN classifier
• CNN for Character Recognition Transfer learning, Using Google Colab
• Building and Training Autoencoder Model
• GAN Applications
• Demo and practice Session on RNN Applications
• RNN Applications
• Practice Session on RL Applications

Topics Covered

• Introduction to deep learning
• Feed Forward NN and Back Propogation, Deep NN
• Regularization and Optimization in Deep NN
• Introduction to CNN
• CNN for Object Detection and Character Recognition
• Introduction to Autoencoders
• Generative Adversarial Network (GAN)
• Introduction to Recurrent Neural Networks (RNN)
• LSTM, GRU, Attention Models, Applications
• Introduction to Reinforcement Learning RL
• An introduction to Q-Learning and Deep RL

List of Speakers

Prof. A. Ojha, Professor, IIITDMJ

Dr. Santosh Vipparthi, Assisistant Professor, MNIT

Prof. Chakravarthy Bhagvati, Professor, Univ of Hyderabad

Dr. S. Murala, Associate Professor, IIT Ropar

Dr. Amar P. Azad, Research Scientist, IBM

Dr. Madan Mohan Dabbeeru, Director, Rakuten, India

Feedback Summary

Excellent speakers with great ideas about the topic.

Major highlight of the programme was joint conduction of the program at various centres and also practice of concepts in lab sessions.

NN and Deep Learning introduction, CNN and RL were the strength of the program.

Suggestions from Participants

Required more time for hands on session.

Basics of NN Before this program would have been added advantage.