HANDS-ON TRAINING LABS AT GTC

THE CONFERENCE IS NOW SOLD OUT. PLEASE JOIN US HERE FOR OUR LIVE KEYNOTE WEBCAST ON 18TH OCTOBER AT 10:00.

TRAINING

GTC Israel will feature valuable hands-on training from the NVIDIA Deep Learning Institute to advance your skills in artificial intelligence and more.

In addition to instructor-led labs, GTC Israel will provide self-paced labs to help you get started.

INSTRUCTOR-LED LABS

Learn how to leverage deep neural networks (DNN) within the deep learning workflow to solve a real-world image classification problem using NVIDIA DIGITS. On completion of this lab, you will be able to use DIGITS to train a DNN on your own image classification application.

17 Oct 2017
10:30

One important area of current research is the use of deep neural networks to classify or forecast time-series data. In this lab, you will learn how to create training and testing datasets and prepare datasets for use with recurrent neural networks (RNNs), which allows modeling of very complex data sequences.

18 Oct 2017
13:30

Explore three approaches to identifying a specific feature within an image using neural networks trained on NVIDIA DIGITS. On completion of this lab, you will understand the merits of each approach and learn how to detect objects using neural networks trained on NVIDIA DIGITS using real-world datasets.

17 Oct 2017
13:30

There are a variety of important applications that need to go beyond detecting individual objects within an image, and that instead need to segment the image into spatial regions of interest. In this lab, you will learn how to train and evaluate an image segmentation network using TensorFlow.

18  Oct 2017
15:30

This lab will show three approaches for neural network deployment. You will learn about the role of batch size in inference performance, as well as various optimizations that can be made in the inference process. You will also explore inference for a variety of different DNN architectures trained in other DLI labs.

17 Oct 2017
16:00

This lab introduces DriveWorks by running the demos which showcase the available modules. You will learn how to integrate sensors using the Sensor Abstraction Layer provided by DriveWorks, followed by the integration of DriveWorks modules into your custom code or applications. Note: the max capacity for each lab is 40 attendees, first-come, first-served.

17  Oct 2017
10:30, 13:30 and 16:00

DLI Labs are BYOC (Bring Your Own Computer) labs. To get yourself prepared, please follow instructions here.

SELF-PACED LABS

These labs are a unique opportunity to get hands-on with specific programming languages, technologies, and domains. Drop by  the Self-Paced Labs area in the Exhibit Hall anytime during exhibit hours to get started.

In this lab we introduce deep learning accelerated by GPUs. We tour popular software frameworks for deep learning by training Convolutional Neural Networks (CNNs) in each framework to classify images.

Learn more >

Learn how to leverage deep neural networks (DNN) within the deep learning workflow to solve a real-world image classification problem using NVIDIA DIGITS.

Learn more >

Learn about the three techniques for accelerating code on a GPU; Libraries, Directives like OpenACC, and writing code directly in CUDA-enabled languages.

Learn more >

Can’t attend GTC? Take a self-paced lab from wherever you are by creating an account using Qwiklabs.

NVIDIA Deep Learning Institute

WANT MORE TRAINING?

The NVIDIA Deep Learning Institute delivers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning. Through self-paced labs and instructor-led workshops, the Deep Learning Institute offers training on the latest techniques for designing, training, and deploying neural network-powered machine learning across a variety of application domains.