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Aims to build strong predictive models that can anticipate the critical opportunity of getting enough funds.

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Crowdfunding_Prediction

Aims to build strong predictive models that can anticipate the critical opportunity of getting enough funds.

One of the biggest challenges for project owners is to raise enough funding to support the work progress. Therefore, the goal of this project is to build strong predictive models that can anticipate the critical opportunity of getting enough funds. This project gives professionals in the crowdfunding platforms and project owners more insights into the characteristics that influence the chance of success in fundraising.

Steps:

  1. Develop a classification model (i.e., a supervised-learning model where the target variable is a categorical variable) to predict whether the variable “state” will take the value “successful” or “failure.”
  2. Develop a clustering model (i.e., an unsupervised-learning model which can group observations together) to group projects together.

The dataset in this project is scraped from Kickstarter, which is a popular crowdfunding platform.

See Crowdfunding Prediction Jupyter Notebook for detailed analysis

All the external data used in this project can be seen at Kickstarter.xlsx

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Aims to build strong predictive models that can anticipate the critical opportunity of getting enough funds.

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