IMPORTANT: You must RSVP to this event before 2:30pm the day of or you will not be permitted to enter the building.  You are more than welcome to bring a guest, but they must also RSVP to this event.

Meetup Description

Introduction to Hierarchical Temporal Memory

Hierarchical Temporal Memory (HTM) is a machine-learning algorithm that mimics the structural and algorithmic properties of the Neocortex. The Neocortex implements common set of algorithms to perform many different intelligent functions such as vision, hearing movement etc. HTM are a type of neural networks. HTM networks consist of layers, regions and hierarchy. HTM is memory-based system. HTMs are trained on lots of time varying data and depend on storing large set of patterns and sequences.

Presenter Bio

Satish Bhat is a Machine Learning Scientist at DST. Prior to DST, Satish spent his career at Adknowledge building recommendation engines for behavioral targeting systems, mining petabytes of data, and building data pipelines in Hadoop that processed billions of events each day. Satish has a Bachelor’s degree in Computer Science from University of Pune and a Master’s degree from University of Missouri-Kansas City. 

Food

DST Systems will be providing pizza and drinks for all to enjoy.

Getting There

We are in the white building.  The main entrance faces south towards 11th street.  There will be a security guard at the door.  Tell the guard your name and proceed up to the 3rd floor where we will be in the conference room.  If your name is not on the list, you will not be permitted to enter.

Parking

Parking is available on the surrounding streets (just watch out for traffic and no parking signs).  There is a parking garage nearby which is often free.  If there is a charge for parking, DST Systems cannot validate your parking so you will have to pay to park.