Machine Learning and Smart Energy; Exploring computer vision APIs w/JavaScript

This month, we have two topics:

1. Machine Learning and Smart Energy by Benjamin Manning

As the need for alternative energy resources begins to increase, the adoption of using solar energy has become a popular alternative for many families and this is causing a fluctuation in the estimated energy needs forecasted by energy companies. This presentation entails using ensemble machine learning methods to build a predictive model that can be used to secure more accurate prediction methods and close the energy estimation gap created by the adoption of solar energy by many households.

Mr. Benjamin Manning is a senior data analytics mentor at the University of Texas-Austin. He has been a machine learning and data analytics consultant for the past fifteen years and holds a master’s degree in engineering with an emphasis on machine learning and artificial intelligence. He is a currently pursuing a PhD in Engineering at the University of Georgia and is a recent Google Internet of Things (IoT) Technology Research Award recipient. Prior to UT he served in various academic and industry positions and has also worked with large national clients on numerous engineering projects since 2001. His main research areas include Knowledge Based Systems, Machine Learning, Artificial Intelligence and the Internet of Things.

2. Exploring computer vision APIs with JavaScript

A quick intro into how computer vision works and then an exploration and a quick comparison of Google Cloud Vision, Microsoft Computer Vision, IBM Watson Visual Recognition, and Clarify. Let's see what they can see!

Pavel Veller is a developer and technologist who has been building things for the web since the late 90s using Java, C#, Ruby, JavaScript and everything in between. Digital architect and a CTO by day and an avid learner by night, his latest interests include deep learning and Elixir.