As a recent project, I created a presentation for an analysis of Kickstarter campaign data in which I was looking for which text features present in the descriptions, titles and blurbs can be used to predict success. The analysis mainly employed NLP techniques and basic machine learning models (linear regression, random forest models). Primarily, I worked to distill complex, technical models into digestible takeaways for a non-technical audience.

1. Recipe for Kickstarter Success
March 1, 2017
Michael Kamradt

2. me
•
•
•
•
•

3. Problem

4. hypothesis

5. Question 1

6. Question 1: What I found
Formatted
title
Un-Formatted
title

7. Question 1: finding

8. question 2

9. question 2: what I found
Average Success Rate per 1,000 characters

10. question 2: what I found
Average Success Rate of projects with and
without first person
funded

11. question 2: finding

12. question 3

13. question 3: what I found
Average Success Rate of projects with and
without “reward” words
funded

14. question 3: finding

15. recap

16. Other things to consider

17. Thank you