Machine Intelligence with Streaming Data
A new approach for anomaly detection and time-based learning
This webinar provides an overview of the current state of HTM, with an emphasis on the software implementation and example applications. The Q&A session at the end of the webinar answers some popular user questions.
Presented by
- Christy Maver (Director of Marketing, Numenta)
- Scott Purdy (Director of Development, Numenta)
Video
Machine Intelligence with Streaming Data from ProHuddle on Vimeo.
About
Links:
Main Event Website
Numenta Event Page
Across every industry, we are seeing an exponential increase in the availability
of streaming, time-series data. The real-time detection of anomalies has
significant practical application. Finding anomalies in such data can be very
difficult, given the need to process data in real time, and learn while
simultaneously making predictions. With the increasing variety of streaming data
sources, automated deployment—without manual parameter tuning—is also becoming
important.