In addition to the features shown in the video, we also worked on implementing an ensemble supervised learning model using scikit-learn, numpy, and pandas, which would take in data from the user like current symptoms, average period duration, average cycle length, in order to predict the user's next period phase. Through the machine learning model, we were hoping to personalize the user's experience to their cycle, allowing for an even better understanding of their cycle and its phases.
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