The Project is aiming to Predict Housing Price in GTA. In order to achieve that we went through several steps: • Cleaned Dataset using Pandas, NumPy, and Seaborn Libraries. • Implemented EDA in order to apply a Machine learning Model. • Applied a Multiple Regression Model, a Polynominal Regression Model, and Classification K nearest neighbor Model. • Built a Support Vector Machines classification model with recall 0.89 to predict the price. • Visualized data using mapping and Folium Library.
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Using Machine Learning Algorithms to predict housing price in GTA, Canada