Challenge 1: sell more cars
Description: Congratulations on deciding to become a tech entrepreneur and starting your first consulting business! After doing some extensive market research in Alberta, you have found that the hottest up and coming industry right now is automotive sales! Thinking long and hard about how you can get your piece of the pie, you have come up with your big idea: You will create a machine learning model to predict people’s car purchasing preferences for marketing!
Timeline: January 28 – February 8, 2021
Evaluation: Percentage of correct preference predictions
Winners: Logan Fairgrieve-Park, Mohamed Mujammil Mohamed Yacoob (Tied)
Challenge 0: SMLB Inaugural Challenge
Description: In this challenge, individuals or teams of up to three will compete to develop the best python based machine learning algorithm in order to determine the price of Edmonton AirBnbs based on a number of descriptive features such as number of guests allowed, neighbourhood, number of beds and more. Teams will be provided with a training dataset in order to train their algorithm so that when given the test set, a prediction will be made about the price of each AirBnb.
Timeline: October 23 – November 8, 2020
Evaluation: Each submission will be evaluated using root mean square error, where the algorithm’s predictions will be evaluated against the test set’s data. The algorithm with the lowest root mean square error will be chosen as the winner of the competition.
2nd Place: Lee Borschneck