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Predict using ML the number of infected people and the number of deaths of coronavirus.
SOFT COMPUTING TECHNIQUES PROJECTS ARCHIVE
My deep learning course work from the following Udemy course: https://www.udemy.com/pytorch-for-deep-learning-and-computer-vision/
We predicted whether there is less chance or more chance of heart disease by exploring different Data Mining techniques like logistic regression, classification trees, and neural networks. We employed various algorithms and choose the model which gives the best prediction results by comparing the accuracy measures to avoid overfitting.
Neural network model for predicting yield per unit area based on the location
CNN and ANN models trained with MNIST dataset.
An aggregation of my experiments in Neural Networks and Deep Learning using TensorFlow.