Graphs and knowledge m anagement have gained significant visibility with the rebirth of artificial intelligence and emergence of cognitive computing. By combining artificial intelligence, big data, graph databases, and dynamic visualizations, we wi ll discuss deploying graph based AI applications as a means to help predict future events across numerous types of industries.
\nKnowledge creat ion via AI and graphs stems from the capability to combine the probability space (i.e. statistical inference on a user’s data) with a knowledge base of comprehensive industry terminology systems. AI using graphs are rem arkable not just because of the possibilities they engender, but also becau se of their practicality. The confluence of knowledge via machine learning, visual querying, graph databases, and big data not only displays links bet ween objects but also quantifies the probability of their occurrence. We be lieve this approach will be transformative across numerous business vertica ls.
\nDuring the presentation, we will describe the graph-based AI co ncepts that also incorporate Hadoop, along with analytics via R, SPARK ML, and other AI techniques for practical Enterprise predictive analytics use c ases.
\n DTSTART:20180424T153000 SUMMARY:Taking Graphs to the Next Level with Artificial Intelligence and Ma chine Learning DTEND:20180424T162959 LOCATION: See Description END:VEVENT END:VCALENDAR