GitHub - omaryashraf5/House-Prices-Prediction-Regression: Models that predict house prices by predicting a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. I have explored regularized linear regression models for the task of prediction and feature selection. I was able to handle very large sets of features and select between models of various complexities. Analyzed the impact of aspects of the data -- such as outliers -- on the selected models and predictions. To fit these models, I have implemented optimization algorithms that scale to large datasets.

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Models that predict house prices by predicting a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performan…