The last decade has witnessed an immense progress in the field of deep learning (DL). The DL models have been successfully deployed in various fields for different classification and regression tasks. Theory and practical knowledge of DL models is absolutely necessary for researchers working in the areas of computer vision, natural language processing, signal processing and robotics. This high-end workshop aims to introduce the participants to the fundamentals of deep learning. The workshop has a balanced focus on theoretical lectures (mathematical preliminaries and network models), hands-on sessions (Python and PyTorch implementations) as well as discussions on state-of-the-art research topics (deep learning applications). After completion of this course, the participants will be comfortable with understanding and PyTorch implementation of CNN, RNN, LSTM and GAN based models. Additionally, they will gain exposure to different research directions that employ such models.
Inauguration: 12 September, 2022 (Monday), 9:30 AM - 10:00 AM
|
Day |
September 2022 |
9:30 AM – 11:00 AM |
11:30 AM – 1:00 PM |
2:00 PM – 5:00 PM |
|
MON |
12 |
Linear Algebra for Deep Learning |
Optimization for Deep Learning |
2:00 PM - 3:00 PM
3:30 PM - 5:00 PM |
|
TUE |
13 |
Artificial Neural Networks, Perceptron, MLP and RBF ANN |
Backpropagation Algorithm, Learning Issues, ANN Evaluation |
Introduction to PyTorch, Experiments with MLP on MNIST and CIFAR10 Datasets |
|
WED |
14 |
Convolutional Neural Networks - Introduction |
Popular CNN Architectures and Applications |
Implementation of CNN Architectures in PyTorch |
|
THU |
15 |
Recurrent Neural Networks, LSTM |
Neural Text Models |
Applications of CNN and LSTM in Audio Processing |
|
FRI |
16 |
Vision and Language |
Generative Adversarial Networks |
Vision and Language: Automatic Image Captioning |
|
SAT |
17 |
Reinforcement Learning - Introduction |
Deep Reinforcement Learning |
Attention Models: Detection and Segmentation in Images |
|
SUN |
18 |
Adversarial Attacks and Defences on Deep Learning Models (
Prof. Arijit Sur ) |
Hardware Realization of Neural Networks |
Evaluation : 2 PM - 2:30 PM Valedictory Session : 3:45 PM - 4:30 PM Role of a Technocrat in a Smart and Intelligent World by Shri Mukul Kanitkar |
