Have you ever wondered how an AI solution is built? In this session we will demystify the process and walk through how machine learning can be applied to solve a real-world problem. Starting from a multi-year dataset of thousands of mechanical devices, we’ll review and explain the steps it took to build a machine learning model that is able to predict when a device is about to fail. Specifically we’ll cover:

* What is AI and Machine Learning?

* Defining the problem

* Feature Engineering

* Model Selection

* Model Training and Evaluation

* Production Considerations

While the use case we will cover was implemented in R, our focus will be on the overall process so you can take what you’ve learned an apply it to your toolset of choice. You’ll leave with a better understanding what AI is and how machine learning works.

Bio:

Juan began his career in the field of bioinformatics — data science applied to biologic problems. Those early experiences opened his eyes to possibilities that the technologies behind AI can accomplish. He has spent his career at the intersection of software development, data management and data science, which has given him the unique ability to design innovative intelligent software systems.

Juan is a Senior Technology Consultant at Omni where he is focused on AI offerings. Prior to Omni, Juan was a consultant focused on the life science and healthcare verticals.

Brought to you by the Fox Valley Microsoft Data Platform Users Group, be sure to sign up for a free membership. We meet monthly at the OMNI Resources office in Appleton, WI. Dinner is provided at no cost.
http://fox.pass.org/

A Practical Introduction to AI for the Data Professional

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