An end-to-end intelligent assistance tool for crowdfunding projects

Estimate the probability of success of crowdfunding projects using machine learning classification algorithms and develop a Ruby library to help users boost their campaigns. This work has been done during my Data Science Internship at DigiSponsor in Paris

• Collect (scrape) crowdfunding project’s data from Kickstarter using python
• Perform exploratory statistics and analysis on the data
• Build a machine learning classifier that estimates the probability of success for different projects
• Build web service using Microsoft Azure REST API to host the trained model
• Integrate the results to the company’s platform using Ruby