The objective of this project is to compare and contrast the predictive performance of different machine learning models, specifically neural networks and gradient boosting models, in the context of forecasting Wikipedia page views. The primary aim is to identify which model type yields superior results in terms of predictive accuracy, which can inform future research and practical applications in the field of web analytics.
The study will involve collecting a dataset of Wikipedia page views over a specified time period, using the mediawiki API.