Time Series Forecasting of Sales Data using Hybrid Analysis

Forecasting of sales data based on time for businesses and organizations is absolutely an efficient thing to be done for the successful market trend analysis, and it will be an added advantage for the manufacturing sector to meet the business needs for an organization. Knowing about the future trends will be a crucial thing for sales and production, hence sales forecasting plays a vital role in achieving higher sales rate and thereby improving the efficiency of the businesses. Using machine learning methods like random forest, linear regression, XG-boosting, K Neighbors regression model, and Keras deep neural network regressor to predict sales for future demands with precision. This Forecasting approach is based on the product attributes, customer information, and various necessary parameters such as data related to product sales, past sales performance, customer demands according to time considering all these factors the analysis were done in the trained data.