Deep Learning | Web Development | Programming Language | Database |
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Report abuseWe train different models and apply techniques gives us better evaluation metrics, and find out the best model which works the best for Parkinson's Prediction System
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This project implements time series analysis techniques to capture temporal patterns and trends in stock price movements and gives a generalized model.
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I have used Mnist digit classification dataset. The model is trained on 60,000 images of 28*28 using RNN. The model accuracy is 97.39 with a loss of 0.099
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Dog vs Cat Classification model trained over MobileNetv2. The model is trained on 2000 images and gives an accuracy of 98.75%
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Human Stress Detection in and through Sleep by monitoring physiological data. The KNN model is working with an accuracy of 100% and random forest model is working with an accuracy of 99.35%.
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