Presented By O'Reilly and Cloudera
Make Data Work
31 May–1 June 2016: Training
1 June–3 June 2016: Conference
London, UK
Stephane Rion

Stephane Rion
Senior Data Scientist, Big Data Partnership

Stephane Rion is a senior data scientist at Big Data Partnership, where he helps clients get insight into their data by developing scalable analytical solutions in industries such as finance, gaming, and social services. Stephane has a strong background in machine learning and statistics with over 6 years’ experience in data science and 10 years’ experience in mathematical modeling. He has solid hands-on skills in machine learning at scale with distributed systems like Apache Spark, which he has used to develop production rate applications. In addition to Scala with Spark, Stephane is fluent in R and Python, which he uses daily to explore data, run statistical analysis, and build statistical models. He was the first Databricks-certified Spark instructor in EMEA. Stephane enjoys splitting his time between working on data science projects and teaching Spark classes, which he feels is the best way to remain at the forefront of the technology and capture how people are attempting to use Spark within their businesses.

Sessions

9:00–17:00 Tuesday, 31/05/2016 - Wednesday, 01/06/2016
SOLD OUT
Training
Location: Capital Suite 17
Stephane Rion (Big Data Partnership)
Average rating: ***..
(3.50, 2 ratings)
The real power and value proposition of Apache Spark is in building a unified use case that combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. Stephane Rion employs hands-on exercises using explore various Wikipedia datasets to illustrate the variety of ideal programming paradigms Spark makes possible. Read more.
9:00–17:00 Wednesday, 1/06/2016
SOLD OUT
Training
Location: Capital Suite 17
Stephane Rion (Big Data Partnership)
The real power and value proposition of Apache Spark is in building a unified use case that combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. Stephane Rion employs hands-on exercises using explore various Wikipedia datasets to illustrate the variety of ideal programming paradigms Spark makes possible. Read more.