This workshop teaches deep learning techniques for a range of computer vision tasks through a series of hands-on exercises. You will work with widely-used deep learning tools, frameworks, and workflows to train and deploy neural network models on a fully-configured, GPU-accelerated workstation in the cloud. After a quick introduction to deep learning, you will advance to: building and deploying deep learning applications for image classification and object detection, modifying your neural networks to improve their accuracy and performance, and implementing the workflow 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.
At the conclusion of the workshop, you will have an understanding of the fundamentals of deep learning and be able to:
Why Deep Learning Institute Hands-On Training?
Introduction to deep learning, situations in which it is useful, key terminology, industry trends, and challenges.
Unlocking New Capabilities
Hands-on exercise: training neural networks to perform image classification by harnessing the three main ingredients of deep learning: deep neural networks, big data, and the GPU
Hands-on exercise: deployment of trained neural networks from their training environment into real applications.
Measuring and Improving Performance
Hands-on exercise: neural network performance optimization and applying DNNs to object detection.
Learn how to setup your GPU-enabled environment to begin work on your own projects. Explore additional project ideas along with resources to get started with NVIDIA AMI on the cloud, nvidia-docker, and the NVIDIA DIGITS container.
Familiarity with programming fundamentals such as functions and variables.