Machine Learning for Black Friday Sales Prediction Framework

understanding the purchasing patterns of various consumers (Dependent variable) In relation to various product utilize their demographic data (IS characteristics the majority of which our self explanatory. This data set is made up of redundant, unstructured, and all values. The retail industry’s domain most frequently uses  machine learning. As it will assist which their inventory management, Financial planning, promotion and marketing, this approach helps to produce predictor that has specific commercial value to store owners. Processing modelling, training, testing and assessing all steps in the development of a model. As a result framework will be created to automate some of these procedure, which will lessen there complexity. For the collection of Black Friday tire sales, the algorithm this chose was Random Forest Regressor, with a least RMSE(root mean square error) value of 2829 and an average score of 83.6%.