University of Connecticut

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Collaborative Classroom Series - Predicting House Prices Using Machine Learning

Tuesday, April 13, 2021
6:00pm – 7:00pm


Machine learning models are masters of pattern-based learning - go find the data that you think matters and let the computer tell you if you can predict the answer! Imagine we are trying to predict house prices in Connecticut. We would want to show the computer a bunch of detailed data (number of bedrooms, age of house, school district quality), along with the thing you are trying to predict (the house price), and let the computer learn the patterns for how to relate the input data to the output. Once the model is trained, you can apply it widely across Connecticut and predict how much a house would sell for before it does. In this workshop, we will show you how to use Python to download datasets, make beautiful visualizations, fit a machine learning model, and show which variables were the most important for making an accurate prediction.

Join us for a collaborative virtual class and discussion with Dr. Dave Wanik, Assistant Professor-in-Residence in the Department of Operations and Information Management. No coding experience or special software required – just sit back, listen and enjoy the material! All students will be provided with the code notebook prior to the workshop.

Register here:


Alyssa Suhr,

School of Business (primary), Executive MBA, Full-time MBA Program, Graduate Business Programs, School of Business Alumni, School of Business Part-time MBA Program

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