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 reusable? Teresa Tung and Jean-Luc Chatelain explain how domain knowledge graphs—the technology behind today's internet search—can bring the same democratized experience to enterprise AI. They then explore other applications of knowledge graphs in oil and 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. While there are myriad benevolent applications, this also ushers in a new era of fake news. Scott Stevenson explores the danger of such systems and details 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. Mingxi Wu outlines the eight prerequisites of a practical graph query language, drawn from six years' experience dealing with real-world graph analytical use cases. Along the way, Mingxi compares GSQL, Gremlin, Cypher, and SPARQL, pointing out their respective pros and cons. Read more.