Endorsed by Curators:
Please join us for an exciting evening to learn more about Deep Learning with TensorFlow through a real-world IoT predictive maintenance scenario fromJustin Brandenburg,Data Scientist at MapR Technologies.
5:30 pm - 6:00 pm:Networking, pizza and drinks
6:00 pm - 6:05 pm:Welcomeby Slim Baltagi from Hexstream
6:05 pm - 7:00 pm:Talkby Justin Brandenburg from MapR
Hexstreamis hosting the event and offering pizza and drinks.
As MapR continues to innovate its Converged Data Platform and how it integrates a globally distributedelastic data plane that not only supports distributed file processing but also strongly consistent geo-distributeddatabase applications with high performance NoSQL document DB, and real-time event streaming capabilitiesin a single cluster, MapR will provide a technical deep dive into these innovations.
In this talk, we'll look at how organizations can leverage IoT and bring compelling insight into their operationsto optimize efficiencies or predict behavior with actionable results with MapR Converged Platform and Deep Learning Models.
We will evaluate and demonstrate a workflow for an IoT predictive maintenance scenario that leverages real-time streaming events and predictbehavior using TensorFlow, Spark and Python. We will showcase an entire data pipeline build for data transformation, model training/testing, and data visualization of results.
Justin Brandenburg is aData Scientist at MapR Technologies.He has experience in a number of data analytics verticalsranging from counter narcotics to cyber analytics where has leveraged machine learning, graph theoryand dynamic programming to pull value from data. He has a undergraduate degree in Economics fromVA Tech, a Masters in Economics from Johns Hopkins University and a Masters in Computational SocialScience from George Mason University.
<a href="https://mapr.com/blog/"></a>How to find us:At the lobby, please ask for the meetup's conference room