this research project aims to investigate the factors that influence the success or failure of Kickstarter projects, using R and Pyhton. We will use a scraped version of the Kickstarter database, available on Kaggle, to model the data and predict the state of a project (i.e., successful, failure, cancelled, suspended)
The outcome of this research will be beneficial for investors and startup owners alike. Investors can use this model to estimate the probability of success for a given project, which will help them make informed investment decisions. On the other hand, startup owners can use this model to calculate the risk associated with their project and take necessary actions to increase their chances of success.
Overall, this research project will provide valuable insights into the factors that influence the success or failure of Kickstarter projects. By analyzing the data and implementing machine learning algorithms, we hope to contribute to the development of the startup ecosystem and promote informed decision-making among investors and startup owners.