This is a Xccelerate Full Time Data Science Bootcamp Cohort 3 group project, that we practice our skills in building machine learning models.
Riding on the Kaggle dataset regarding kickstarter projects, we try to build ML models to address:
- Creators' concern about the fund amount being raised
- Backers' concern about whether a campaign be successful
Skills: data understanding, visualisation, data transformation, machine learning models
For detail please refer to the jupyter notebook here.
- Data Cleaning
- Data Visualization
- Regression model for Creators (Linear Regression, Random Forest Regressor)
- Model 1: using predicting features that are only available before the campaign starts
- Model 2: include features that are only available AFTER the campaign starts (explanation included)
- Linear Regression
- Random Forest Regressor
- Summary of Regression problem
- Classification model for Backers (Logistic Regression, Random Forest Classifier
- Model: all are based on features available prior to campaign starts
- Summary of Classification problem
- Improvement
Our presentation of the project can be found here. Google Slides