Spark, Zeppelin and Cassandra

Because we have had problems with no-shows, this time we will explicitly take a register and take note of no-shows. Please make sure you change your RSVP if you later find you cannot make it. RSVPS open at 10am Monday 4th July.

Speaker: Kostas Perifanos

Title: Stylistics with Spark and Zeppelin

Given a dataset of approximately 10 million short texts produced by 190.000 authors, what can we say about their writing style? In this talk we explore this problem using statistical NLP and Machine Learning with Apache Spark and Apache Zeppelin

Kostas has been working in publishing and research for more than 15 years. He joined Royal Mail in 2015 and he is currently involved with user behaviour analysis, ranking and optimization among other stuff. Prior to Royal Mail, he worked at MailOnline and was involved in a broad range of projects from European FP6 research programs to EdTech, Analytics, Search, Predictive Modelling using fancy tools and technologies, machine learning and AI. He is interested in Deep Learning, Distributed Computing, Search, Predictive Analytics, Natural Language Processing, AI and optimisation.

Speaker: Duy Hai Doan

Title: Spark/Cassandra/Zeppelin for particle accelerator metrics storage and aggregation

Abstract: At Synchrotron in France, we collect sensor data for every shoot. Since a shoot duration is very brief (a few millisecs), we need a continuously available data store to record metrics data, thus Apache Cassandra. The analytic component is handled by Apache Spark and vizualiation by Apache Zeppelin.

Duy Hai Doan is an Apache Cassandra Evangelist at DataStax. He spends his time between technical presentations/meetups on Cassandra, coding on open source projects to support the community and helping all companies using Cassandra to make their project successful. Previously he was working as a freelance Java/Cassandra consultant.