When: 13:30 Thursday 21 March 2019 - 13.30 Friday 22 March 2019
Best for: Exclusively for verifiable researchers from academic and government institutions, academic staff, and students. Please register with your academic email address: firstname.lastname@example.org
About This Workshop:
This workshop teaches you to apply deep learning techniques to 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, followed by modifying your neural networks 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.
At the conclusion of the workshop, you will have an understanding of the fundamentals of deep learning and be able to:
Implement common deep learning workflows, such as image classification and object detection
Experiment with data, training parameters, network structure, and other strategies to increase the performance and capability of neural networks
Integrate and deploy neural networks in your own applications to start solving sophisticated real-world problems
Familiarity with basic programming fundamentals such as functions and variables
Workshop Setup Instructions:
- Bring your laptop!
- Before coming to the course:
Create an NVIDIA Developer account at http://courses.nvidia.com/join.
Make sure that WebSockets works for you:
Test your laptop at http://websocketstest.com
Under ENVIRONMENT, confirm that “WebSockets” is checked yes.
Under WEBSOCKETS (PORT 80), confirm that “Data Receive,” “Send,” and “Echo Test” are checked yes
If there are issues with WebSockets, try updating your browser. We recommend Chrome, Firefox, or Safari for optimal performance.
3. Once onsite, visit http://courses.nvidia.com/dli-event and enter the event code provided by the instructor.