SALES PREDICTION

Introduction

   Sales prediction is an important part of modern business intelligence. It can be a complex problem, especially in the case of lack of data, missing data, and the presence of outliers. Sales prediction is rather a regression problem than a time series problem. Practice shows that the use of regression approaches can often give us better results compared to time series methods. Machine-learning algorithms make it possible to find patterns in the time series. We can find complicated patterns in the sales dynamics, using supervised machine-learning methods. 

Program Explanation

This is a program to predict sales based on the features of the available dataset. The idea is to predict sales using processed data and form models using the Linear Regression method for several different features resulting from feature selection, then evaluate the model and choose the best model.

Project Status: [Completed]

Getting Started

1. You can access the raw data here within this repo.
2. All of the scripts are being kept here.

Result

This Machine Learning model achieves a accuracy of 84% using Linear Regression Algorithms.

I hope this will be useful someday, thankyou for seeing !✌🏻