18.45 – 19.00: Welcome coffee;
19.00 – 19.50: “Small changes in big data”, Andrei Zhabinski, Adform.
We will discuss why function derivatives are so important in modern machine learning, review backpropagation algorith and build our own TensorFlow, with blackjack and Jacobian.
19.50 – 20.10: Coffee break;
20.10 – 21.00: “Apache Kylin – distributed analytics engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop”, Sergey Kovalev, Solution Architect at EPAM Systems.
During the presentation we will discuss, what is Apache Kylin, how it is differ from other analytics engines on top of Hadoop and why do we need one more.
Will make architecture overview and main features highlights. Design example of OLAP cube, cover typical use cases, drawbacks and limitations.
Free event, no registration required.
Language is Russian.