CDHK Lehre (ed.): Workshop Agenda: Cognitive Computing, Machine Intelligence, and Deep Learning Neural Networks - Current state of the art and impacts of AI on business, management, manufacturing, automation and society - CDHK Tongji, 同济大学  - Shanghai 14.-17.10.2018

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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YEAR: 2018
PERM. URL: http://gcc.upb.de/CDHK/Blockseminar/CDHK-K_Pool.nsf/index/WINFO-2018
 
GCC's Wirtschaftsinformatik-Workshops at CDHK/Tongji Shanghai 2006 - 2018: Database 'CDHK K-Pool', View 'GCCNC_ThemesCompact', Document 'Blockseminare / Workshops Information Management' AGENDA & IMPRESSIONEN, Photos, Videos
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Log Okt. 2018
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CDHK - Chinesisch-Deutsches Hochschulkolleg
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Prof. Dr. Ludwig Nastansky, emer.
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Groupware Competence Center (GCC)
University of Paderborn, Germany
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Adjunct Professor
Business Information Systems
Tongji-Universität l 同济大学
Chinesisch-Deutsches Hochschulkolleg
CDHK l 中德学院
Tongji University, Shanghai
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2006 2007 2008 2009
2010 2011 2012 2013-03
2013-10 2013-11 2014 2015
2016 2017 2018 2019
LOGBUCH DES WORKSHOPS WIRTSCHAFTSINFORMATIK

Cognitive Computing, AI/Machine Intelligence,
and Deep Learning Neural Networks

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

CDHK Blockveranstaltung, Tongji University
Siping Campus, CDHK-Gebäude, Raum 305 307
14.-17.10.2018
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Prof. Dr. Guanwei Huang
Metro Stiftungslehrstuhl für Innovationsmanagement und Wirtschaftsinformatik
CDHK, Tongji University
Shanghai, China
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Workshop-Verlauf - Lehrplan - Überblick
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Status 25.10.18 VS-3.6
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Prezi Next Homepage - 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)
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    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 ... and more
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    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!
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    Class of 2018
    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)
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    5. Miscellaneous – Open Issues
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    6. 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 WINFO/AI Workshop 2018
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ProfNastansky-Syllabus-WS2018_VS-3.2.pdf
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Für deutsche Gaststudenten/Austauschstudenten:
  • ECTS-Optionen unter Pkt. 5
  • Anmeldefrist für Projektarbeiten Fr 19.10.2018
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