Every day, new data is created. As data increases in quantity, it becomes more complex and ultimately more difficult to process in fast, meaningful ways. Machine learning to the rescue! Machine learning models can quickly and accurately analyze large datasets. In this workshop, you will get a glimpse into how we can teach machines to analyze complex scenarios at large scale. After cleaning and organizing your data, you will train and test some machine learning models—and even publish your predictions online for others to explore.

Instructor – Brian Sletten
Brian Sletten is a liberal arts-educated software engineer with a focus on forward-leaning technologies. His experience has spanned many industries including retail, banking, online games, defense, finance, hospitality and health care.
He has a B.S. in Computer Science from the College of William and Mary and lives in Auburn, CA. He focuses on web architecture, machine learning, resource-oriented computing, social networking, the Semantic Web, data science, 3D graphics, visualization, scalable systems, security consulting and other technologies of the late 20th and early 21st Centuries.
He is also a rabid reader, devoted foodie and has excellent taste in music. If pressed, he might tell you about his International Pop Recording career.
You can learn more about Brian at https://www.linkedin.com/in/bsletten/

[eventID:7823]

source