Demand Forecasting is the process in which historical sales data is used to develop an estimate of an expected forecast of customer demand. I worked on the Store Item Demand Forecasting dataset available at Kaggle (https://www.kaggle.com/c/demand-forecasting-kernels-only) . The dataset consists of 10 stores and 50 items and their respective sales for years 2013-2017. In my project i used the plotly and seaborn visualization libraries for plotting which are an excellent tool to get insights into the data. Feature engineering was performed to get the right features for predicting the sales.I used the following ML models : Gradient Boosting Regressor ,Decision Tree Regressor ,Linear SVR ,Random forest Regressor and compared the performance . Finally, deep learning implementation is also done using LSTM.
SharadChoudhury/Store-Sale-Demand-forecast
Demand Forecasting is the process in which historical sales data is used to develop an estimate of an expected forecast of customer demand. I worked on the Store Item Demand Forecasting dataset available at Kaggle (https://www.kaggle.com/c/demand-forecasting-kernels-only) . The dataset consists of 10 stores and 50 items and their respective sales . In my project i used the plotly and seaborn visualization libraries for plotting which are an excellent tool to get insights into the data. Feature engineering was performed to get the right features for predicting the sales.I used the following ML models : Gradient Boosting Regressor ,Decision Tree Regressor ,Linear SVR ,Random forest Regressor and compared the performance . Finally, deep learning implementation is also done using LSTM.
Jupyter Notebook