Home
Agenda
Speakers
Sponsors
Tracks
Prizes
FAQs
Sponsor
MediaKit
REGISTER NOW!
WP7 Accelerator Lab!
Attendees
Tulsa TechFest 2011
Featured Speakers
Bio
Seth Juarez, Technical Evangelist, DevExpress
My name is Seth Juarez. I currently reside in Salt Lake City (en route to Glendale CA) and work as a Technical Evangelist for DevExpress I received my Bachelors Degree in Computer Science at UNLV with a Minor in Mathematics. I recently completed my Masters Degree at the University of Utah and am continuing on to a PhD in the field of Computer Science. I currently am interested in Artificial Intelligence specifically in the realm of Machine Learning. I've been married now for 8 years to a fabulously beautiful girl and have two wonderful daughters and a son.
Sessions
C# Design Patterns
Instead of boring the audience with a multitude of slides, this session will feature live coding to illustrate some of the well known gang-of-four design patterns in C#. Attendees will not only be able to see a live demonstration of these patterns, but through the demonstrations will be empowered to find areas in their own software where these patterns will benefit the quality and re-usability of their code all in a highly interactive session.
Oct 7th
The Kinect API
The Kinect is a little marvel of technology that has been released to the masses. This session will delve into foundational concepts surrounding this little gadget and describe Microsoft's Kinect API in a user friendly manner. Attendees will learn how to access the device's depth, camera, and skeletal information to create novel user interfaces to their software.
Oct 7th
Machine Learning for .NET
The purpose of this session is to demystify the central ideas behind pattern recognition and machine learning by demonstrating two key elements of the same: namely classification and clustering. Most developers shy away from such algorithms simply because of their perceived difficulty while missing the inherent simplicity of these approaches. The first part of the session will demonstrate how a computer can learn from labeled examples in order to predict appropriate labels for future examples. The second portion will deal with learning the structure of data without having to know anything about it a priori. The intent of the session is to empower developers to learn certain techniques that will allow for exciting and novel features in any software they develop in the future.
Oct 7th
Proud Sponsors