Posted by Syedali Fathima
Jul 6, 2020

Workshop on Fundamentals of Deep Learning for Computer Vision

Hosted by : eLearning

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Payment Information: www.payumoney.com/events/#/buyTickets/courses.nvidia.deeplearning

About the workshop/course:
The Workshop offers Hand's on experience on the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities.
In this course, you’ll learn the basics of deep learning by training and deploying neural networks using NVIDIA DLI GPU accelerated deep learning platform.

To know more about the course:
https://courses.nvidia.com/courses/course-v1:DLI+C-FX-01+V2/about  

Course Content:
Day1: Course Enrolment and Introduction: Basics of AI, ML and DL, Difference between ML and DL, GPU importance
Day2: Artificial Neural Networks: Introduction to Neural Networks – Perceptron - Activation functions - Backpropagation.
Day3: Fundamentals of Deep Learning: Biological inspiration for deep neural networks(DNN) - Convolution neural networks (CNN).
Day4: Training DNNs with big data - Image Classification - Deploying DNN models - Optimizing DNN performance.
Day5: Assessment project for certification: Train and deploy a deep neural network.

Resource Person:
Dr. Syed Ali Fathima S J, Assistant Professor, Department of CSE, Kumaraguru College of Technology, officially been granted NVIDIA Deep Learning Institute(DLI) University Ambassadorship and Certified Instructor. DLI Ambassadors are a select group of DLI Certified Instructors to offer world-class Deep Learning training to the academic community through DLI instructor-led workshops and meetups using proven DLI cloud-based GPU training platform and lecture materials. 

Requirements: Laptop and Internet connection of nominal speed 

Expected Outcomes:
At the conclusion of the course, the students will be able to:

  •  Understand common deep learning workflows, such as image classification and object detection.
  •  Earn NVIDIA DLI Certification to recognize subject matter competency and support professional career growth.

Expected Audience: Only Academicians
Students, Research Scholars, and Faculty from any discipline interested to explore Deep Learning and having familiarity with any programming fundamentals.

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