Sensors, Spark and Kafka: Applied Machine Learning


Details
Please Join us at the Twin Cities Big Data Meetup as we bring you a deep discussion on the real-world technologies that underlie IoT (Internet of Things). Working with real-time, streaming data from mobile phone sensors, and using tools that you can use yourself, we walk through the process of building a machine learning solution with Spark and Kafka to collect and analyze user activity. If you are using Kafka, Spark, or any real-time data technologies, or even if you are just trying to get a better understanding of them, this event is for you.
Bio:
Norbert Krupa is an experienced sales engineering professional, defining technical solutions that meet business and technical requirements of existing and prospective customers. In his current role, Norbert works hands-on with diverse organizations, demonstrating how to harness the power of data. Norbert holds an MS in Computer Science from Northeastern Illinois University.
Here is the link to the deck:
https://talend365.sharepoint.com/departments/mar... (http://meet.meetup.com/wf/click?upn=pEEcc35imY7Cq0tG1vyTtxRtaA-2FCDlxCxaRC26HNzfnxW5SzmIv2GKMppEALQn0BKhYvJcHAOPTCJa-2FPMkRS5E2YwtywLHQpEpBZHbB-2FmyuOVLEHfYekpxpExZWnFIEf7itiLe8guMNmHm58-2FElNF1XA48QTj6S900yvtAs-2BM5UAzNeR1-2F1ymX-2Bqzhvri-2FTrx2K0Tn-2BSYfQXRa2rvs7Z-2B-2BkyO1HuDHhqnMr8qHzBJHk-3D_Ocn7HtknIK8x9ikEBU9E2flmLZT2CxKCQyJTwXsY6ELroV-2Bf-2BNny6rLQ23QwHlaXVFpGsUWZOinFpiKoZBKty5T9zoc2dNVfi9IljfbpsMn9viDPePCzYr368XENCWGJgRbhsEd8nK14LzdG-2FlEwbLSxkhh64B71d5NZrIFFwoNnmD3-2FdNrpnpxx0MutjKblVHLBL6BDtNLCC1rHJlWWwbBLywbdD4Sine-2FyKVIAIpw-3D)
Here is a video of Norbert's past presentation:
https://youtu.be/9otVSVtcF0g (http://meet.meetup.com/wf/click?upn=pEEcc35imY7Cq0tG1vyTt-2BenqPd7ckPElOK0jGjK-2FYeb8JN1nWY4wDbxX4s51XKj_Ocn7HtknIK8x9ikEBU9E2flmLZT2CxKCQyJTwXsY6ELroV-2Bf-2BNny6rLQ23QwHlaXVFpGsUWZOinFpiKoZBKtyxsURxB9ZCroHJeVH2yAYTEoc7zv0Y2-2BJUcB1L0uOhuLw8PHzL9O1AyuzpElCHbbmNU4rDazLG7sm5O0zOY86JGeAHOg-2BFMYZheVLRurKLNEo-2BxeX0YLWbF0AFSigclE0yAKHvxAeZGco0bQy1WyEsc-3D)
Agenda:
5:45 Door opens
5:45 - 6:30 Signup and food
6:30 - 7:30 - presentation
7:30 -8:00 - wrap up
Please arrive through front door and signup at the reception. Somebody will escort you to the cafeteria.
Door will be closed after 6:30 pm and you cannot enter venue after 6:30 pm.
Pizza and Drinks will be served.

Sensors, Spark and Kafka: Applied Machine Learning