Fundamentals of Deep learning for Computer Vision

This workshop teaches you to apply deep learning techniques to a wide range of computer vision tasks through a series of hands-on exercises. You will get to work with widely-used deep learning tools, frameworks, and workflows by performing neural network training and deployment on a fully-configured GPU accelerated workstation in the cloud. After a quick introduction to deep learning to start the course, you will advance to building and deploying deep learning applications for image classification and object detection, followed by modifying the applications to improve their accuracy and performance, and finish by implementing the workflow that you have learned on a final project. At the end of the workshop, you will have access to additional resources to create new deep learning applications on your own.

  • Duration: 8 hours
  • Certification: Upon successful completion of this workshop, you will receive NVIDIA DLI Certification to prove subject matter competency and support professional career growth
  • Prerequisites: Familiarity with basic programming fundamentals, like functions and variables
  • Languages: English
  • Tools, libraries, and frameworks: Caffe, DIGITS

Content Outline

Introduction (45 mins)

  • Course Overview
  • Getting Started with Deep Learning

Unlocking New Capabilities (120 mins)

  • Biological inspiration for Deep Neural Networks (DNNs)
  • Training DNNs with Big Data

Unlocking New Capabilities (40 mins)

  • Deploying DNN models

Measuring and Improving Performance (100 mins)

  • Optimizing DNN Performance
  • Incorporating Object Detection

Summary (20 mins)

  • Summary of Key Learnings

Assessment (60 mins)

  • Assessment Project: Train and Deploy a Deep Neural Network

Next Steps (15 mins)

  • Workshop Survey
  • Setting up your own GPU enabled environment
  • Additional project ideas
  • Getting Data

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