Sickness Detection with 80% Val Accuracy. Trained on (25% of available train data~5GB for 'Pfizer Digital Medicine Challenge'). Reached to accuracy of 80% in this Demo/Prototype
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Updated
Sep 9, 2020 - Jupyter Notebook
Sickness Detection with 80% Val Accuracy. Trained on (25% of available train data~5GB for 'Pfizer Digital Medicine Challenge'). Reached to accuracy of 80% in this Demo/Prototype
Speech Emotion Recognition (SER) using CNNs and CRNNs Based on Mel Spectrograms and Mel Frequency Cepstral Coefficients (MFCCs)
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