Severo Ochoa & GPU CoE Training: Getting Started with Deep Learning (NVIDIA)

Date: 26/Apr/2017 Time: 09:00

Place:

Campus Nord, Building C6, room E101. Start at 9:00am

Target group: Beginner,  no prior knowledge of Deep Learning is required.

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Objectives

Strictly through registration. Start 9:00am.

We will introduce the rapidly developing technology of Deep Learning accelerated by GPUs. Recent advances in Deep Learning have led to a step change in performance in a number of machine perception tasks including visual perception, speech recognition, and natural language understanding after decades of slow progress in these areas. The catalyst for this progress is the advent of big data via the internet, algorithmic advances and dense computation via GPUs.

The tutorial introduces the machine learning workflow and provides hands-on experience with using deep neural networks (DNN) to solve a real-world image classification problem. You will walk through the process of data preparation, model definition, model training and troubleshooting, validation testing and strategies for improving model performance. On completion of this lab you will have the knowledge to use NVIDIA DIGITS to train a DNN on your own image classification dataset.

Academic Staff

Frédéric Parienté, Accelerated Computing at NVIDIA