Using Machine Learning to Classify Strava Activities

SUMMARY - As smartphones become more powerful, many apps are utilizing trained machine learning models to conduct inference in real time to improve customer experience. This project aims to solve a small annoyance I found with the Strava app by designing a light-weight machine learning model that classifies my Strava activities to their appropriate activity type (run, hike, bike) so I don't have to, and is simple enough that a typical smartphone could run the model in real time, onboard. Several classifiers are trained and tuned including random forest, XGBoost, Support Vector Machine (SVM), logistic regression and multi-layer perceptron. The final model meets the above stated needs with over 95% accuracy and an inference time of 1.6 seconds.

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