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Online Training Program on Advanced Machine Learning for Biosignal Data by NIT, Raipur [Oct 8-12]: Register by Oct 5: Expired

About

The Electrical Engineering Department & Information Technology Department, National Institute of Technology (NIT), Raipur is organizing an Online Training Program on Advanced Machine Learning for Biosignal Data from October 8 to 12, 2020.
National Institute of Technology Raipur (Formerly Government Engineering College Raipur), situated in the capital of a newly incepted state of Chhattisgarh, has proven to be “Avant-grade’ in the field of science and technology over the past few decades in this region.
With sweet memory of the foundation ceremony by our president Hon’ble Dr. Rajendra Prasad on 14th September 1956. the institute started with two departments namely Metallurgical and Mining Engineering. Later the inauguration of the Institute building was done by our Prime Minister Hon’ble Pt. Jawahar Lal Nehru on 14th March 1963. From 1st December 2005, the institute has become the National Institute of Technology.

Course Objective
  • The aim of this virtual/ online training program is to provide exposure to both basics and recent advances in machine learning and their applications to biosignal data i.e. 1D, 2D (image), and 3D (video) medical data to the students, budding researchers from both academics and industry as well as faculty members.
  • People from both medical and engineering communities can get benefited from this program.
  • This workshop mainly divided into three parts, advanced machine learning algorithms, basic to advanced recent studies on biomedical signals and images, tools for implementation & virtual demo on biomedical signals and images.
Theme

In the present scenario, the medical disease prognosis, detection, and diagnosis suffers from many human errors and looking into the poor patient-doctor ratio worldwide, the development of computer-assisted technologies is the only solution. Hence, any academic and industry research is going hand on hand to develop such technologies and large work is going on their validation in a real-time scenario, their generalization with minimal computational efforts on a single platform.
In view of that, machine learning techniques are being used at large and they are being further developed to cater above tasks with ease. Such very recent development in deep learning which is being vastly being explored now, having advantages of no feature engineering, intelligent deeper learning, learning migration, and many more.

Topics
  1. Introduction to advanced machine learning
  2. Introduction to deep learning
  3. Applications to biopotentials
  4. Applications to medical images
  5. Online demo/ training on the implementation of advanced machine learning methods in python and MATLAB.
Sessions
  • Advanced Machine Learning-I
  • Advanced Machine Learning-II
  • Advanced Machine Learning Applications for Medical
  • Advanced Machine Learning Applications for Biopotentials-I
  • Advanced Machine Learning Tools & Algorithms
Who can Attend?

UG/ PG Students, Research Scholars, Academicians, and Industry are invited to apply.

Registration Fees
  • Students (UG): Rs. 118
  • Students (PG): Rs. 236
  • Ph.D. Scholars: Rs. 354
  • Faculty Member: Rs. 590
  • Industry Delegate: Rs. 1180

Registration Fees Payment can be made to the account of Director NIT Raipur; Account No.: 38027633250; IFSC: SBIN0002852; Branch: SBI GCET RAIPUR.

Registration
  1. Knowledge of the basics of machine learning, computational platforms like python, MATLAB will help participants to benefit more from this course.
  2. E-Certificates will be issued to the participants only after attending the complete course.
  3. To register for the course, click here.
Contact

Phone Number: 7903631620
Email ID: nlondhe.ele@nitrr.ac.in
 
For full notification, click the link below.

Online Training Program on Advanced Machine Learning for Biosignal Data by NIT, Raipur

 
 
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Online Training Program on Research Scholars’ Week: Applied Sciences & Humanities by NIT, Kurukshetra [Sept 23-27]: Registrations Open.

 
 

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