This course is designed to provide exposure to the fundamentals of Deep Learning and Applications. Participants will learn Introduction to Machine Learning & Artificial Neural Networks Convolutional Neural Networks Autoencoders and Generative Adversarial Networks Recurrent Neural Networks CNN Application to Classification and Detection problems.
Hands-on training and practice sessions will help participants gain confidence in Python concepts, their simulation, and implementation including sessions. The course will be useful for the faculty of engineering and sciences who are interested in learning Deep Learning and Applications from Industry perspective.
- Introduction to Machine Learning & Artificial Neural Networks
- Convolutional Neural Networks
- Autoencoders and Generative Adversarial Networks
- Recurrent Neural Networks
- CNN Application to Classification and Detection problems.
Who can Attend?
The program is open to the teachers of engineering colleges from Electronics and Communication Engineering. Research scholars and Industry personnel working in the concerned/allied discipline can also attend.
- There is no registration fee is charged for attending this program.
- However, a candidate should submit a Demand Draft(In favor of “Director, NIT Patna” payable at Patna)/CBS-Cheque of Rs.1000/-along with the application form and the same will be handed over to the participant on the last day of the training.
- A filled-in form of application in the prescribed format duly signed should be handed over at the registration desk on the first day of FDP.
- Interested candidates can download the registration form by clicking here.
- Certificate for participation as well as for Satisfactory performance will be given to the participants subject to fulfillment of attending all sessions, submission of assignments and clearing the test(s).
- No TA/DA will be paid to the participants.
- Working Lunch, Tea & Snacks would be provided during the training at VNRVJIET campus.
Phone Number: 9866940403
Email ID: email@example.com