My recent submission to the Future Ready Data Challenge conducted by Air Liquide. I achieved an overall position of 4th among 300 + participants.
Challenge: Predicting monthly energy consumption demand of Air Liquide customers using explanatory variables such as Market domain, Time stamp, Type of Gas, Sum of Sales.
Approach: Using time series forecasting approach along with machine learning techniques to predict the corresponding monthly energy consumption demand of each requested customer.