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NVIDIA DEEP LEARNING INSTITUTE - Deep Learning Hands-on Workshop
Thu 25 May 2017, 09:30 – 17:30 CEST
NVIDIA Deep Learning Institute (DLI) offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning. DLI and AddFor are excited to announce this one-day practical Deep Learning workshop in Milan on May 25th 2017.
In this full-day workshop, you will learn to
- Understand general terms and background of deep learning
- Leverage deep neural networks (DNN) within the deep learning workflow to solve a real-world image classification problem
- Measure object detection approaches in relation to three metrics: model training time, model accuracy and speed of detection during deployment
- Take three approaches for neural network deployment: DIGITS and Caffe, Caffe, through its Python API and NVIDIA TensorRT™
NOTA: QUESTO CORSO SARA' TENUTO IN LINGUA ITALIANA
NOTICE: THIS TRAINING WILL BE DELIVERED IN ITALIAN
09:30 DL Demystified + Applied DL (lecture)
11:00 Image Classification with NVIDIA DIGITS (lab)
12:30 Pausa Pranzo
13:30 Object Detection with NVIDIA DIGITS (lab)
15:15 Neural Network Deployment with NVIDIA DIGITS and TensorRT (lab)
17:00 Chiusura, Commenti e Domande
17:30 Fine Lavori
Content level: beginner/intermediate
DLI Workshop Attendee Instructions
You must bring your own laptop to this workshop.
Make sure your laptop is ready to go prior to the workshop by following these steps.
Create a qwikLABS account by going to https://nvlabs.qwiklab.com/ using the same email address as you have for the attendee information in event registration.
Ensure qwikLABS runs smoothly on your laptop by going to http://websocketstest.com/
Make sure that WebSockets work for you by seeing under Environment, WebSockets is supported and Data Receive, Send and Echo Test all check Yes under WebSockets (Port 80).
If there are issues with WebSockets, try updating your browser. Best browsers for qwikLABS are Chrome, FireFox and Safari. The labs will run in IE but it is not an optimal experience.
Who is this presentation for?
- Data scientists, developers and researchers
- Basic knowledge of data science and machine learning
- C++ programming experience