Workshop on

Deep Learning Concept &
CNN implementation

5th March, Duration: 6:00 HRS - MRIIRS, Faridabad

Register Now

Deep Learning Concept & CNN implementation

The 6 hours hands on training workshop teach you how to implement and deploy an end-to-end project while working on a prebuild dataset. The workshop is suitable for individuals with keen interest to work in the field of data science and machine learning.

DATE 5th March 2019

LOCATION MRIIRS

SPEAKER Mr. Sujit Roy

Speaker

We are bringing you the perfect combination of content and experience to ignite your
heart equip your mind and spark your skill.

Sujit Roy Computer Scientist(PhD)

Mr. Sujit Roy has an experience of 5 years in Research and Development in the field of Computer Science. A ceaseless aspirant for knowledge, he’s a developer, a programmer and has overseen SRInnoxy Corporation as Director, R&D, Computer Science Head, MRIIC and guided multiple projects with IIT Madras and IIT Patna.
Salient features of his experience include the areas of Deep Learning, Biomedical Research, Fluid Interface, Brain Computer Interfacing, Image Processing and Holography among others. He has experience in formulation and implementation of ML/DL frameworks into healthcare, IOT and Robotics domains. He is also considered a strategist for business development and hence has completed several business plans, customized market segment and industrial collaborations. He has also received funding for multiple projects from both Government and private sectors. He has 5 filed patents and 2 copyrights to his name. He has also accomplished 30 research projects, majority of which have fetched numerous awards, and few have also made it to the market.
Currently, he’s pursuing PhD in Computational Neuroscience at Ulster University and IIT Kanpur under UKIERI Fellowship. He has keen interest and a proven track record for translating complex ideas into slick.

Topics Covered

Whether you’re new to programming or a pro in Machine Learning, this workshop gives you a touch of every flavour a data scientist should have.

Topics

  • Classifiers
  • CNN – Mathematical and implementation
  • Data structure
  • Image pixel mapping
  • Intro to EEG data
  • CNN classification

About Conference

We will cover the basics of deep learning, without any assumptions about the level of the participants. Beginners are welcome. We will also cover fully connected neural networks - convolutional neural networks - regularisation techniques: dropout, learning rate decay, batch normalisation - recurrent neural networks - natural language analysis, word embeddings - transfer learning - image analysis - image generation - and many examples.

Conference Schedule

  • Day 1 - 1st Half
  • Day 1 - 2nd Half
  • Day 1 - 1st Half
    09:30 - 10:30 Introduction to Python and Matlab toolbox for Deep Learning
    10:30 - 11:30 Classification approach on data (Including code)
    11:30-12:30 Emperical and theoretical discussion of CNN (including code)
    12:30 - 01:00 Break
  • Day 1 - 2nd Half
    01:00 - 01:30 Data Inquiry
    01:30 - 02:30 and cnn classification design and requirement (Image and EEG)
    02:30-03:30 Lets Discuss and Compete

Time left until the conference start

5th March 2019, Deep Learning and CNN

Confirm your presence at workshop 5th March 2019

* In case of Half Ticket, the remaining payment should be done before the workshop

Frequently asked questions

Some frequently asked questions for you.

Is the workshop suitable for me?

The workshop is suitable for beginners as well as for those who have deep interest in the learning new and advance technology.

Registration fee through instalment?

Students have the choice to pay the fee in two installments.

Mode of payment?

Registration fee can be done through online paytm or by cash.

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Contact Info

Dear programmers, you are most welcomed to join us at the event. Have a pleasant experience.

Manav Rachna International Institute of Research and Studies
Delhi Suraj Kund Road, Sector 43,
Faridabad, Harayana

Phone: (+91) 9873932539, 8588883950
Email : info@HelixSmartLabs.com