One of Unilever’s brands is going through some major changes in Business Execution plans and will like to know: What are the major drivers for sales(EQ)? Knowing the drivers, how can they predict future sales for the next 6 periods?

Python - Pandas, Numpy, Scikit-learn, Matplotlib and Seaborn Google Cloud Platform to run the models - Compute and Storage

The top five drivers for determining sales are:

• Median_Rainfall
• Social_Search_Impressions
• pct_PromoMarketDollars_Category
• Inflation
• EQ_Category

• Feature Importance of a model [model.feature_importances_]
• Seaborn’s(python library) Correlation matrix with heatmap

The top five models used for determining sales are:

• RandomForestRegressor
• GradientBoostingRegressor
• LinearRegression
• Support Vector Regressor *MLPRegressor

out.csv is the final output file.