One of the hottest topics in technology right now is Machine Learning. But what does that mean? What is learning? And how does a machine learn?
During this MeetUp we will define and gain an intuition for Artificial Intelligence, Machine Learning, and Deep Learning. We will explore the differences between supervised and unsupervised learning and discuss the challenges faced when developing Machine Learning algorithms. A simple regression example will be used to see many of these concepts in practice. We will finish with a discussion on Artificial Neural Nets and why they have become so popular in recent years.
This talk is intended to give you the language and foundation to start your own exploration into Machine Learning; if you so desire. The slides and sample code can be found here: https://github.com/kylinmb/IntroductionToMachineLearning
Kyli McKay Bishop is currently a graduate student at the University of Utah where she is studying data analysis, machine learning, and data visualization. She is a research assistant at the Scientific Computing and Imaging Institute where she is currently working to design and develop a data analysis and visualization tool to assist in the engineering design pipeline. Prior to beginning her graduate studies she worked in industry as a lead SDET for six years.
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