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Two-Days Workshop on Basics of Deep Learning and its Applications

A two Days Workshop was organised by the Department of Computer Science and Engineering on 19th March- 20th March 2019 sponsored by TEQIP III. The workshop was held in the Conference Hall of the univeristy. Sixth-semester and fourth-semester students of CSE Department participated in the workshop.

About the Workshop

The Two-Days’ Workshop on Deep Learning and its Applications was hosted with the prime intention to introduce the exciting applications of industrial-research works carried out using feature engineering and machine learning techniques regarding deep learning to the students.
Starting from the basics of Machine Learning and Neural Networks, the resource persons delivered the required preliminaries smoothly. The main topics delivered were Convolutional Neural Nets, Recurrent Neural Nets, Autoencoders, Restricted Boltzmann Machines, etc. Applications in the domains of Natural Language Processing, Computer Vision, Path Planning, were also discussed.

Aim and Objectives
  1. Learn the basic principles of neural computing based machine learning techniques
  2. Learn how to use neural computing in solving computational problems like Text Mining, Sentiment Analysis, Object Recognition.
  3. Learn the basics and applications of CNNs, RNNs, andAutoencoders.
Resource Persons

1. Dr. Sanasam Ranbir Singh, Associate Professor, Dept. Of CSE, IIT Guwahati.
2. Dr. Khelchandra Thongam, Assistant Professor, Dept. Of CSE, NIT Manipur.
3. Dr. Kishorjit Nongmeikapam, Assistant Professor, Dept. Of CSE, IIIT Manipur.


1. Jimmy Laishram, Head and Assistant Professor, Dept. Of CSE, MTU.
2. Chiranjiv Chingangbam, Assistant Professor, Dept. Of CSE, MTU.
3. Debina Laishram, Assistant Professor, Dept. Of CSE, MTU.

Workshop Content
Day 1 [ 19th March ] Day 2 [20th March 2019]
Session-I (10:00 AM-1:00 PM): (By Dr. Kishorjit Nongmeikapam)
  • The Journey of Machine Learning
Session-I (10:00 AM-1:00 PM): (By Dr. Sanasam Ranbir Singh)
Introduction to Deep Architecture of AI
  • Review on Backpropagation.
  • Sequence Model.
  • Convolutional Model.
  • Auto-Encoder.
  • Attention Model.
Session-II (2:00 PM-5:00 PM): (By Dr. Khelchandra Thongam)
  • Basics of Artificial Neural Networks.
  • Single Layer Perceptron.
  • Multi Layer Perceptron.
  • Self Organizing Feature Map.
  • Hopfield Neural Network.
  • Convolutional Neural Network.
  • Applications
Session-II (2:00 PM – 5:00 PM): (By Dr. Sanasam Ranbir Singh)
  • Brief discussion on a few of its applications.
  • Representation Learning
  • Text Mining Applications.
  • Network Related.
  • Speech Related.
  • Image Related.
Participants’ Feedback

All the students’ gave positive feedback. In terms of applicability of the topics that were delivered, the instructor’s communication with the students, the speed and pace at which the topics were presented were all positively acknowledged by the students. The students also requested a follow-up workshop with more industrial applications.

Future Action Plan

1. The department intends to hold a five-day workshop on deep learning with industrial partners like NVIDIA and INTEL.
2. The department also intends to include hands-on practice on the follow-up workshops.
3. The follow-up workshops should also be open to faculties and research scholars of institutes within or outside our state.


In all perspectives, the workshop was a success. The students were highly motivated and encouraged by the lectures that were delivered by the resource persons. The intermingling flavours of the concepts and applications that were presented on the different sessions made a clear picture for the students that the scope of computational sciences has a lot to offer for solving intricate problems related to many scientific as well as social fields. The resource persons presented not only academic knowledge but also shared their valuable experiences relating to the research they carried out. The objectives of the workshop were achieved and for the students, their hopes and vision were kindled.



Last Updated on April 4, 2024 by Web Admin