K-nearest neighbors ML algorithm to predict car market prices
This project uses K-nearest neighbors machine learning algorithms to predict the market price of cars. Part 1 is based on the Dataquest mission 155 guided project and returns the optimal training features and k-values for predicting a car's market price using test/train validation. Part 2 expands on this guided project further to find the optimal training features, k-value and number of k-folds using a more robust K-fold cross validation technique to measure the model's accuracy.