Presented are two submissions for the Data Science module at the University of Lincoln one was implmented in RStudio and one in Azure ML. The first is unlabbeled data and employs common Data Science disciplines for prediction. The second is for Bike Rental Demand Prediction using Azure ML Studio, it shows data preprocessing, feature engineering, outlier removal, visualisation, algoritm comparisons, model selections and time series modeling.
Both papers can be viewed and read in the root of this repository.