ELECTRONICS AND ICT ACADEMY AT NATIONAL INSTITUTE OF TECHNOLOGY PATNA
Setup Under Scheme of Department of Electronics and Information Technology
Ministry of Communications and IT, Govt. of India
Setup Under Scheme of Department of Electronics and Information Technology
Ministry of Communications and IT, Govt. of India
Principal Coordinator :
Joint-Principal Coordinator :
Academic (student/faculty): 500 INR
Industry People/ Others: 1000 INR
Foreign Participants: 4000 INR
Bank Name: Allahabad Bank (Merge to Indian Bank)
Account Name: NIT Patna
Account No.: 50380476798
IFSC Code: IDIB000B810
(i) Industry support from NVidia, MathWorks (MATLAB) (ii) Dr. Anupama Ray, IBM (iii) Dr. Ritu, Intel, (iv) Prof. R. Venkatesh Babu, IISc Banglore (v) Dr. Biplab Banerjee IITB Experts from host institutes- (iii) Prof. R. Balasubramanian, IITR (iv) Prof. Aparajita Ojha, IIITDMJ (v) Dr. Partha Pratim Roy, IITR (vi) Dr. Santosh K. Vipparthi, MNITJ
| S.No. | MODULES TOPICS |
|---|---|
| 1 | Artificial Neural Networks (ANNs)- Introduction to Deep Learning and Motivation. Brief introduction of Artificial Neural Networks (ANN), Perceptrons, Multilayer perceptron (MLP), Back propagation training for MLP, Stochastic gradient descent. Applications to some practical classification problems. Hands on: Demonstration and implementation of Shallow and Deep architecture, introduction to Python, Tensorflow and Keras.. |
| 2 | Regularization, Hyperparameter Tuning and Autoencoders - Deep Feed forward Networks - Regularization - drop out, Minibatch gradient descent, RMSProp and Adam optimization, Autoencoders and Their Types Hands on: Hyper parameter tuning and regularization practice, Minibatch gradient descent, Autoencoders |
| 3 | Convolutional Networks - The Convolution Operation, Pooling, Basic architecture of a Convolution Neural Network, Variants of the Basic Convolution Model, Evolution of Convolution NN Architectures - AlexNet, ResNet and other architectures. Hands on : Convolution neural network application using Tensorflow and Keras, Autoencoders using CNN, Building an application for classification and feature extraction. |
| 4 | Sequence Modeling- Recurrent and Recursive Nets - Unfolding Computational Graphs, Recurrent Neural Networks, The Long Short-Term Memory and Other Gated RNNs. Hands on : Language modeling and machine translation, Chatbots. |
| 5 | Generative Adversarial Networks, Object Detection Algorithms- GAN and their variants- R-CNN , YOLO and SSD Hands on– Object detection, Realistic Image Generation and face recognition |
Dr. Bharat Gupta (CI E & ICT Academy, NIT Patna)
Email: bharat@nitp.ac.in
Dr. M.P Singh (CI E & ICT Academy, NIT Patna)
Email: mps@nitp.ac.in
Website: http://old.nitp.ac.in/ict/index.php
Contact us :
Electronics and ICT Academy
National Institute of Technology, Patna
AshokRajpath, Patna 800005
Email: eictapatna@nitp.ac.in
Website: http://old.nitp.ac.in/ict