Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK

Schedule: Graph technologies and analytics sessions

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17:2518:05 Wednesday, 1 May 2019
Teresa Tung (Accenture Labs), Jean-Luc Chatelain (Accenture)
How do enterprises scale moving beyond one-off AI projects to making it re-usable? Teresa Tung and Jean-Luc Chatelain explain how domain knowledge graphs—the same technology behind today's Internet search—can bring the same democratized experience to enterprise AI. Beyond search applications, we show other applications of knowledge graphs in oil & gas, financial services, and enterprise IT. Read more.
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11:1511:55 Thursday, 2 May 2019
Data Science, Machine Learning & AI
Location: Capital Suite 17
Scott Stevenson (Faculty)
Modern deep learning systems allow us to build speech synthesis systems with the naturalness of a human speaker. Whilst there are myriad benevolent applications, this also ushers in a new era of fake news. This talk will explore the danger of such systems, as well as how deep learning can also be used to build countermeasures to protect against political disinformation. Read more.
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14:0514:45 Thursday, 2 May 2019
Data Science, Machine Learning & AI
Location: Capital Suite 14
Mingxi Wu (TigerGraph)
Graph query language is the key to unleash the value from connected data. In this talk, we point out 8 prerequisites of a practical graph query language concluded from our 6 years experience in dealing with real world graph analytical use cases. And compare GSQL, Gremlin, Cypher and Sparql in this regard. Read more.