Kickstarter Success

Kickstarter Success is a machine learning powered application to help you predict whether your kickstarter campaign will be successful based on several factors: campaign name, description, category, fundraising goal, country, and duration.

The data science team:

  • Used Kickstarter dataset to predict the percentage of success of a campaign using TfidfVectorizer and Spacy models to do natural language processing on campaign descriptions.
  • Created and deployed Random Forest models using a Flask  API on Heroku so the back end can make requests and return predictions.

You can check out the project at  https://kickstart-success.netlify.com 

Role: Machine Learning Engineer

DS Tech Stack: Python, SQL, Flask, Heroku, Scikit, Spacy, TfidfVectorizer, Plotly, AWS (Sagemaker, S3)

Timeline: 1 week

The GitHub repo with all of the project notebooks and code can be found here.

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