4 - 5 OCTOBER 2017 / EXCEL LONDON

NVIDIA Deep Learning Institute



DEEP LEARNING WORKSHOPS

Teaching You To Solve Problems With Deep Learning

Learn how to design, train, and deploy neural network-powered artificial intelligence in your applications.

 
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 IP EXPO Europe are excited to announce these one-day practical Deep Learning workshop on both days of IP EXPO Europe, Wednesday 4th and Thursday 5th October 2017 at ExCeL London from 9:00am-5:30pm.

There are two levels of workshop available, Fundamentals for beginners and the Intermediate for those with a higher level of experience in Deep Learning.

Places come at a price of £385 per session.

The workshops take place in the upstairs suites with the Fundamentals course in SG13 and the Intermediate course in SG15.

First Click REGISTER FREE for IP EXPO Europe and then select the NVIDIA Register & Training option to pay for the workshop after registration.

 

WHO IS IT FOR?

Data Scientists:
- Experts in collecting and analyzing data.
- May have experience with previous Machine Learning techniques.
- Needs to shift approach from hard-coded feature classifiers to data-driven deep neural networks.

Software Developers:
- Implements custom code for deep learning solutions.
- May also fill role of data scientist.
- Needs to learn how to integrate and optimize trained neural networks into apps/services for deployment.

System Architect:
- Domain expert in their field of study.
- May have experience with HPC / parallel computing.
- May also fill roles of data scientists and developer.
- Needs to learn how to apply deep learning in their field of study.





FUNDAMENTALS (BEGINNERS)

Wednesday 4th October & Thursday 5th October 2017
9:00am-5:30pm
Location: Room SG13

 

WHAT TO EXPECT

Content level: Beginner
Pre-Requisites: Technical background and basic understanding of deep learning concepts

This hands-on introduction to deep learning is designed to take a learner from interest to ability. Attendees will train a neural network on a GPU within the first hour and have deployed a high performing network to production by the end of the day. Throughout the experience, learners will:

-          Implement common deep learning workflows such as Image Classification and Object Detection.
-          Manipulate how networks learn to improve performance using the DIGITS interface.
-          Modify internal layers of neural networks to adapt to new problems using the Caffe framework.
-          Deploy open-source and learner-trained networks to start solving real-world problems using pyCaffe and TensorRT.

WORKSHOP AGENDA*:

9:00    Deep Learning Demystified and Applied Deep Learning (lecture)
9:45    Break
10:00  Image Classification with DIGITS (lab)
12:00  Lunch
1:00   Object Detection with DIGITS (lab)
3:00   Break
3:15   Neural Network Deployment with DIGITS and TensorRT (lab)
5:15   Closing Comments & Questions
5:30   End
*Agenda timing is subject to instructor preference

DLI Workshop Attendee Instructions:

  • You must bring your own laptop to this workshop.
  • Create an account by going to https://nvlabs.qwiklab.com/ prior to getting to the workshop.
  • Make sure your laptop is set up prior to the workshop by following these steps:

- Ensure websockets 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 or trying a different browser.  The labs will not run without WebSockets support
- Best browsers for the labs are Chrome, FireFox and Safari. The labs will run in IE but it is not an optimal experience.

IMPORTANT: Please remember to sign in to nvlabs.qwiklab.com using the same email address as for event registration, since class access is given based on the event registration list.

Adam Grzywaczewski
Adam Grzywaczewski

Deep Learning Solution Architect

NVIDIA

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Adam Grzywaczewski

Adam is an experienced applied research scientist specialized in Machine Learning and Information Retrieval with extensive Deep Learning/Big Data/Software Development/System Architecture background. Currently working for NVIDIA as a Deep Learning Solution Architect, Adam is the primary support to a wide range of customers (from private, public and educational sector) in delivering their machine learning / deep learning solutions.

Past positions have included building Machine Learning / Big Data capabilities for the biggest UK government departments as Senior Data Scientist at Capgemini and prior to that Adam's role in the Jaguar Land Rover Research Centre oversaw a variety of internal and external projects and contributed to the self-learning car portfolio. Previous roles include Software Developer and Architect positions delivering solutions for organisations such as O2/Telephonica, DEFRA, LOCOG and LSC/SFA.

Adam Grzywaczewski holds a PhD in Information Retrieval.

Are you interested on learning more? Explore the Fundamentals workshop

We look forward to seeing you at IP EXPO Europe for the NVIDIA Deep Learning Fundamentals workshop.

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INTERMEDIATE

Wednesday 4th October & Thursday 5th October 2017
9:00am-5:30pm
Location: Room SG15

 

WHAT TO EXPECT

Content level: Intermediate
Pre-Requisites: Nvidia’s Deep Learning Fundamentals Workshop OR a working understanding of Deep Learning Fundamentals such as:
- Training basic networks
- Searching hyperparameters to improve performance

Generating descriptions of scenes requires both computer vision and natural language processing. After an introduction to TensorFlow, learn to work with natural language and then to combine workflows and datatypes to generate captions for images and video. Building on concepts from Deep Learning Fundamentals, you will learn to:
-          Implement common deep learning workflows such as Image Segmentation and Text Generation.
-          Manipulate features of both networks and training to improve performance.
-          Compare image vs. text based data prep, data ingestion, and training workflows
-          Combine workflows to solve more complex, 'multi-sensory' problems.

Problem specific skills such as:
-          Extracting high level features from images
-          One-hot sentence encoding
-          Concatenating input data

WORKSHOP AGENDA*:

9:00    Best Practices in Deep Learning (lecture)
9:45    Break
10:00  Image Segmentation with TensorFlow (lab)
12:00  Lunch
1:00   Text Generation with TensorFlow (lab)
3:00   Break
3:15   Image and Video Captioning by Combining CNNs and RNNs (lab)
5:15   Closing Comments & Questions
5:30   End
*Agenda timing is subject to instructor preference

DLI Workshop Attendee Instructions:

  • You must bring your own laptop to this workshop.
  • Create an account by going to https://nvlabs.qwiklab.com/ prior to getting to the workshop.
  • Make sure your laptop is set up prior to the workshop by following these steps:

- Ensure websockets 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 or trying a different browser.  The labs will not run without WebSockets support
- Best browsers for the labs are Chrome, FireFox and Safari. The labs will run in IE but it is not an optimal experience.

IMPORTANT: Please remember to sign in to nvlabs.qwiklab.com using the same email address as for event registration, since class access is given based on the event registration list.

Jonas Loof
Jonas Loof

Deep Learning Solution Architect

NVIDIA

View Speaker

Jonas Loof

Jonas Lööf is a Deep Learning Solution Architect at NVIDIA, where he helps guide customer decision making on both hardware and software in their deep learning projects.

Before joining NVIDIA, Jonas has worked in research and development, applying deep learning in the fields of speech recognition and natural language processing, both in a startup environment and the corporate world.

Jonas holds a doctoral degree in computer science from RWTH Aachen University, where he worked on acoustic model adaptation for speech recognition.

Are you interested on learning more? Explore the Intermediate workshop

We look forward to seeing you at IP EXPO Europe for the NVIDIA Deep Learning Intermediate workshop.

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NVIDIA Deep Learning Institute

The NVIDIA Deep Learning Institute delivers hands-on training for developers, data scientists, and engineers. The program is designed to help you get started with training, optimizing, and deploying neural networks to solve real-world problems across diverse industries such as self-driving cars, healthcare, online services, and robotics.



 
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