CDHK Lehre (ed.): Workshop Agenda:Cognitive Computing, Machine Intelligence and Deep Learning Neural Networks - Current state of the art and impacts on business, management, manufacturing, automation and society - CDHK Tongji, 同济大学  - Shanghai 11.-14.10.2017

Goal: Conveying to students the broader picture and current state oft the art of the fast changing areas currently defined by cognitive computing, machine learning, artificial intelligence, and - especially – deep learning neural networks. The depth of discussion is on the level of a survey, introd...

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GCC's WKMS-Workshops at CDHK/Tongji Shanghai 2006 - 2017: Database 'CDHK K-Pool', View 'GCCNC_ThemesCompact', Document 'Blockseminare / Workshops Information Management' AGENDA & IMPRESSIONEN, Photos, Videos
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Log Okt. 2017
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CDHK - Chinesisch-Deutsches Hochschulkolleg
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Groupware Competence Center (GCC)
University of Paderborn, Germany
Prof. Dr. Ludwig Nastansky
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Prof. Dr. Pei Wang-Nastansky
Florida International Univ., Miami, USA
Tianjin Univ. of Commerce, China
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2006 2007 2008 2009
2010 2011 2012 2013-03
2013-10 2013-11 2014 2015
2016
LOGBUCH DES WORKSHOPS WIRTSCHAFTSINFORMATIK

Cognitive Computing, Machine Intelligence
and Deep Learning Neural Networks

- Current state of the art and impacts on business, management, manufacturing, automation and society -

CDHK Blockveranstaltung, Tongji University
11.-14.10.2017

Metro Stiftungslehrstuhl für Innovationsmanagement und Wirtschaftsinformatik
CDHK, Tongji University
Shanghai, China
Prof. Dr. Guanwei Huang
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Workshop-Verlauf / Lehrplan - Überblick
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Status 26.09.16 VS-2.2
Cognitive Computing, Machine Intelligence
and Deep Learning Neural Networks

Prezi Next Homepage

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AI-Topics (c) The Economist
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Agenda
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1. Introduction
(AI - Rise of the Machines, Machine Learning (ML) vs. Deep Learning (DL), AI and DL – A Conceptual Overview)

2. Underlying and Defining Core Developments and Technologies
2.1. Big Data and worldwide Distribution of Data Centers
2.2. Processors: From CPU over GPU to TPU and FPGA

3. Theory – Research
3.1. The „Dark Ages“ of DL – Lessons of Perseverance in Research
3.2. Network of Researchers Driving DL(amongst others: Geoffrey Hinton, Yann LeCun, Joshua Bengio, Andrew Ng, Jürgen Schmidhuber, Fei-Fei Li)
3.3. DL Concepts(DL Tutorial, Feed Forward & Backpropagation, Convolution & Convolution Tutorial, DL Live Layer Activation and Interaction, DL Glossary)
3.4. Speech and Sound
3.5. Tutorial / Survey: Current DL Network types, Imagenet Winners, Live Demos (ConvNetJS Autoencoder, ConvNet Visual Recognition, Image Kernels visualization)
3.6. DL Godfather Geoffrey Hinton finally says: Start it over – especially Backpropagation!

4. Applications and Society
4.1. Business (DL Startups, Marketing, Fraud Prevention, ...)
4.2. Industry – Manufacturing (Automotive, ...)
4.3. Society (Education and Policy, Health and Medical, Impact on Jobs – Automation Anxiety)

5. Miscellaneous – Open Issues
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Code-Examples und References exemplarily based on „MATLAB“ DL-Libraries
(DL Toolbox, Visualize ConvNet Features, WebCam Image Recognition, Object Detection, Creative Art „Deep Dream“)

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Syllabus
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ProfNastansky-Syllabus-WS2017_VS-2.3.pdf
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Für deutsche Gaststudenten/Austauschstudenten:
  • ECTS-Optionen unter Pkt. 5
  • Anmeldefrist MO 17.10.2017
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