2018-09-13 Fundamentals of Deep Learning for Multiple Data Types (HDLW4S18)

Date:Thursday, Sept. 13, 2018, 9:00-17:30
Location:LRZ Building, Garching/Munich, Boltzmannstr. 1, LRZ Hörsaal H.E.009 & Seminarraum 1 H.E.008
Contents:

The Leibniz Supercomputing Center (LRZ) is the computer center for Munich's universities and for the Bavarian Academy of Sciences and Humanities.It is also a national center for High Performance Computing.   NVIDIA Deep Learning Institute (DLI) offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning. LRZ and DLI are excited to announce this one-day practical workshop - Fundamentals of Deep Learning for Multiple Data Types at LRZ on Sept. 13th, 2018, exclusively for verifiable students, staff, and researchers from any academic institutions (For industrial participants, please contact NVIDIA for industrial specific training).

In this full-day workshop, you’ll learn how to train a network using TensorFlow and the MSCOCO dataset to generate captions from images and video by:

  • Implementing deep learning workflows like image segmentation and text generation
  • Comparing and contrasting data types, workflows, and frameworks
  • Combining computer vision and natural language processing

Upon completion, you’ll be able to solve deep learning problems that require multiple types of data inputs.

Workshop Agenda:

9:00 Lecture
9:45 Break
10:00 Image Segmentation with TensorFlow (with coffee break)
12:00 Lunch
1:00 Word Generation with TensorFlow
3:00 Break
3:15 Image and Video Captioning by Combining RNNs with CNNs
5:15 Closing Comments & Questions
5:30 End

Content level: Beginner

Pre-Requisites: complete DLI computer vision workshop or have completed a university machine learning course, familarity with TensorFlow will be a plus as all the hands-on sessions are using TensorFlow. For those who do not program in TensorFlow, please go over TensorFlow tutorial: https://www.tensorflow.org/tutorials/, especially the "Learn and use ML" section.

IMPORTANT: To reserve your seat, you MUST register at the LRZ registration with a valid email address. Please choose course HDLW4S18. Additionally, please follow these pre-workshop instructions:

  • You must bring your own laptop to this workshop.
  • Create an account at http://courses.nvidia.com/join
  • Ensure your laptop will run smoothly 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. If you have any questions, please contact Marjut Dieringer at mdieringer"at"nvidia.com
  • Please remember to sign in to http://courses.nvidia.com/join using the same email address as for event registration, since class access is given based on the event registration list. Please beware that for the adminstrative reasons, after you register at nvlabs.qwiklab.com, Nvidia will use your email address to contact you for the final feedback of the workshop..

On the day of the workshop, please bring your student/academia id. The number of participants is limited to 100.
This workshop is brought to you by:

Looking forward to seeing you at LRZ.
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.

Language:English
Teacher:Dr. Yu Wang, LRZ and Nvidia University Ambassdor
Registration:Via the LRZ registration form. Please choose course HDLW4S18.