Conclusion
Although there are few limitations through our project (elaborated in "Future Work" section), our "Wake Me Up" application indeed captures the desired graphs' difference, and performs well in machine learning process to predict optimal time to wake up a user in the context of domestic environment. Moreover, building the Android alarm clock application allows user to set up desired time range to wake up.
The key components of this project are (1) CV MSE algorithm in analyzing photos, (2) LASSO machine learning model in predicting data, and (3) Flask framework in communicating between Android application and back-end machine learning process.
The key components of this project are (1) CV MSE algorithm in analyzing photos, (2) LASSO machine learning model in predicting data, and (3) Flask framework in communicating between Android application and back-end machine learning process.