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Simulations for the paper "Deep Learning for the Gaussian Wiretap Channel by Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder"
This project employs machine learning to forecast housing prices in California. By scrutinizing location, housing details, and demographics, it constructs various regression models like Linear Regression, KNN, Random Forest, Gradient Boosting, and Neural Networks. These models offer invaluable insights to optimize predictive real estate investment
This is the assignment works of Convolutional Neural Networks using TensorFlow.