Google Analytics Customer Revenue Prediction
- Analyzed raw log data from GStore (faced to normal customers) to predict revenue per customer.
- Preprocessed the raw data (2.4GB) based on Pandas and Numpy and made data visualization based on Matplotlib and Seaborn module.
- Improved the data procession speed based on parallelization using Hadoop and PySpark.
- Trained model to predict based on LightGBM, XGBoost and CatBoost, assembled these models to improve 20% performance.
