In this project, I took in data related to home sales in order to develop a model to predict future home sales. We had to wrnagle the data and transform it, perform EDA and look at various correlations between features in order to set up a machine learning (polynomial linear regression) model on which to train and then create predictions. We performed feature engneering and scaling in the process.
Programming, Python, Databases, Statistics, Probability, SciPy, Numpy, Pandas, Seaborn, Matplotlib, Scikit-learn, Data Modeling, EDA, Data Visualization, Data Summarization, Data Reporting, Regression, Supervised ML, Communication