Deep Learning and Applications
Principal Coordinator : Prof Aparajita Ojha |
Aug 23 to Sep 3 2021 | |
Joint Principal Coordinators : | ||
Dr. Santosh K. Vipparthi Dr. Prithwijit Guha |
Dr. M P Singh Prof RBV Subramanyam |
Dr. Amey Karkare Dr Raksha Sharma, |
Last Date of Registration: 21 Aug 2021
Course contents:
Introduction to Machine Learning & Artificial Neural Networks: Overview of machine learning, Supervised and unsupervised learning , Artificial Neural Networks, Feedforward Neural networks, Gradient Descent and the back propagation algorithms, Regularization and Optimization. Difference between typical machine learning and deep learning
Practice Session: Introduction to Python Programming, Tensorflow and Keras.
Making a Neural Network, training and testing. Saving the best weights and model
Convolutional Neural Networks: Convolutional Neural Network (CNN), Convolution/Pooling layers, Activation maps, CNN as a feature extractor, Some Standard CNN architectures like AlexNet, VGGNet, GoogLeNet, ResNet and more recent networks
Practice Session: Building a CNN model, CNN for image classification. Using
Googel Colab for building and training Deep Learning Models.
Autoencoders and Generative Adversarial Networks: Autoencoders (AEs), Undercomplete and Overcomplete AE, Convolutional AE, Regularization, Sparsely regulated AEs, Denoising and Stacked AE. Generative Adversarial Networks (GAN), Variants of GAN.
Practice Session: Using pretrained models, Transfer learning, Applying
GoogleNet and ResNet for specific problems. Using Autoencoders
Recurrent Neural Networks: Brief Introduction to Recurrent Neural Networks, LSTM, GRU and their applications in machine translation, language modelling and sentiment classification.
Practice Session: Building an AI application for sentiment classification from travel\hotel website user feedback data.
CNN Application to Classification and Detection problems: Object detection algorithms, R-CNN, Faster R-CNN, YOLO and SSD. Hands on– Object detection.
Practice Session: Installing Darknet framework on your laptop, how to use YOLO for object detection.
Key Features:
- Online / Live lectures sessions by subject experts.
- Comprehensive tutorials and practice notes.
- Online lab and training sessions.
- Follow up sessions and discussion forums on research problems and internships.
Course Fee Details:
Academic (student/faculty): 500 INR
Industry People : 1000 INR
Others : 1000 INR
Foreign Candidates Registration Fee-
SAARC/African countries candidates fee
Faculty/PhD-Scholars/students - Rs. 500/-
Others - Rs. 1000/-
For US & rest of the countries
Fee - $ 60 or £ 50
Online payment details:-
Bank Name: INDIAN BANK
A/C No. : 50302042708
IFSC Code: IDIB000M694
Branch: Mehgawan, IIITDM Branch
Core Team Members, E&ICT Academy:
Prof Aparajita Ojha
Email: aojha@iiitdmj.ac.in
Prof. Vijay Kumar Gupta
Email: vkgupta@iiitdmj.ac.in
Prof. P.N. Kondekar
Email: pnkondekar@iiitdmj.ac.in
Dr. Atul Gupta
Email: atul@iiitdmj.ac.in
Dr. Prashant Kumar Jain
Email: pkjain@iiitdmj.ac.in
Website: ict.iiitdmj.ac.in
Contact us :
Ritu Bhatnagar
Business Manager,
Electronics and ICT Academy
PDPM Indian Institute of Information Technology,
Design and Manufacturing, Jabalpur,
Dumna Airport Road, Jabalpur 482005
Phone:+91-8458849734 ;
0761-2794255
Email: academy@iiitdmj.ac.in
Email: academyjbp@gmail.com
Website: ict.iiitdmj.ac.in