The sales_forcasting project using machine learning. Two learn More Visit the github page of upgini("https://github.com/upgini/upgini") You can also see the data from the Kaggle ("https://www.kaggle.com/competitions/demand-forecasting-kernels-only/data?select=train.csv") The dataset we will make use of contains 5-years worth of product sales data. Our goal is to effectively forecast the future sales of those produts for the next 3-month. To achieve this goal we will be making use of a state-of-the-art gradient boosting algorithm as well as a python librabry called "Upgini",for data enrichment.
During the Project, we will see:
- How to efficiently use popular python libraries like pandas
- How to use catboost
- How to enrich data with Upgini
- Import of data enrichment
- What are SHAP values
- What are SMAPE values
- How to split time-series datasets into training and testing sets
- How to train and test models.