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Summer School - Big Data and Machine Learning, 2-6 July 2018, Germany

Summer School - Big Data and Machine Learning, 2-6 July 2018, Germany

Germany 01 Jun 2018
COMPETENCE CENTER  FOR SCALABLE DATA SERVICES  AND SOLUTIONS (ScaDs)

COMPETENCE CENTER FOR SCALABLE DATA SERVICES AND SOLUTIONS (ScaDs)

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OPPORTUNITY DETAILS

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Deadline
01 Jun 2018
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Big Data and Machine Learning

From June 30th to July 6th, 2018 the two in Germany based Big Data Competence Centers ScaDS Dresden/Leipzig and BBDC are organizing the fourth international summer school on Big Data and Machine Learning in its summer school series.The event aims at graduate students, Ph.D. students, researchers as well as well as practitioners starting or being active in the field of Big Data and Machine Learning. The program offers inspiring insights into the area by selected research keynotes from international experts combined with industrial talks.  Prior to the summer school, there will be a "streamline" hackathon for hands-on development of an application for real-time analytics of streaming data.  Furthermore, there will be plenty of opportunities to exchange ideas and to discuss the topics with other participants and speakers. The summer school also hosts several social activities such as a city walk and a dinner in a traditional restaurant.

Important Dates

  • Hackathon: June 30th- July 1st 2018
  • Summer School: July 2nd- July 6th 2018

Locations

The big data Hackathon and the Summer School will be held at the University of Leipzig 

Topics and Program Highlights

The Hackathon will focus on the practical application of stream-based event processing. 

  • Overview to building complex real-time data analytics pipelines based on open-source cluster-computing frameworks 
  • Implementation by using such frameworks
  • challenge: pick one or more real-time data sources and build real-time analytics workflows or tools, which improve strategic planning or decision making. Source are either provided by the samples or can self-chosen and optional historical data sources can be used.

  The topics of the summer school include:

  •  Data Mining in Stream Data
  •  Machine Learning for the Sciences
  •  Declarative machine learning with Apache SystemML
  •  Confidentiality and Integrity of Cloud Databases
  •  Visual Analytics for Big Data
  • -Cipher-based Graph Analytics on Spark
  •  Web-scale information extraction
  •  Big Data Integration

 

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