That's right, we already offered this talk. But it's back by popular demand with a more specific focus on Machine Learning. Enjoy!
Getting the Data: Tracking commercial aircraft in near real-time using a Raspberry Pi, Kafka & Vertica
Using relatively simple to acquire hardware and software, this presentation shows how it possible to track the flights of commercial aircraft in near real-time. Automatic Dependent Surveillance Broadcast (ADS-B) data from aircraft transponders is captured and decoded using a Raspberry Pi, delivered through a series of Apache Kafka Topics before being loaded into a Vertica database.
With real-time streaming combined with billions of rows of historical data, we look at how this can be manipulated and used with relative ease using the inbuilt analytics and machine learning capabilities of Vertica for data capture, enrichment, measuring and preparing. Demonstrating examples of simple SQL functions for handling time series data, gap filling and interpolation and outlier detection.
From the early 1980s, Mark worked with Michael Stonebraker's Ingres RDBMS and then a number of column-store big data analytic technologies. In 2016, he joined HPE Big Data Platform as a Systems Engineer specializing in Vertica and Vertica SQL in Hadoop, and from September 2017 followed Vertica as it moved over to Micro Focus.
Mark frequently delivers talks at the London, Cambridge and Munich Big Data & Machine Learning Meetups, the British Computer Society - Advanced Programming Specialist Group, Vertica Forums and elsewhere.
Putting the Data to Work: Anomaly Detection with Time Series+production.
Building on Mark's presentation, we will look at a practical use case of anomaly detection. Going first through exploratory steps, we will walk you through the definition of our anomaly detection case, how this is achieved using time series data, as well what are the best way of putting such a model into production.
Silviu is working as a data scientist at Dataiku. Coming from a business-oriented background, with an MSc in Business Analytics from the University of Manchester, he transitioned to a more technical focus while working on an optimization problem together with ARM. Before coming to Dataiku, Silviu was involved with social housing organizations to develop their data science capabilities.