Data Science-Powered Apps for Internet of Things
The Internet of Things (IoT) continues to provide value and hold promise for both the consumer and enterprise alike. To succeed, any IoT project must concern itself with (1) how to ingest data, (2) build actionable models, and (3) react in real-time.
In this talk, Chris describes approaches to addressing these concerns through a deep-dive into an interactive demo centered around classification of human activities. See the guts of such applications and learn about the tools that will enable you to build an application like this yourself!
These include: (1) collecting streaming smartphone data, (2) the process of training and building machine learning models in real-time, and (3) an application that scores real-time. For each of these he will cover the necessary components of the entire IoT stack of ingesting, storing, and processing big data - all in real-time using the open-source Pivotal Cloud Foundry and Big Data Suite.