SALES FORECASTING FOR COMPANY USING MACHINE LEARNING

SALES FORECASTING FOR COMPANY USING MACHINE LEARNING

Tejaswini C S, Amrutha O, Harshini J C, K Gouri, Gagan T N

Department of ISE

Vidya Vikas Institute of Engineering and Technology, Mysore

Abstract - For modern retailers operating a huge chain of stores, accurate sales forecasting is key to the development of the business, even to its success or failure.

Sales forecasting allows companies to efficiently allocate resources such as cash flow and production and create a sound business plan. In this paper, we propose an efficient and accurate sales forecasting model using machine learning.

Machine learning is a branch of AI that enables the machine to automatically learn from data, improve its performance based on previous experience and make predictions. Machine learning involves a series of algorithms that work with a huge amount of data. These algorithms are fed with data to train them and based on the training, they create a model and perform a specific task. These ML algorithms help in solving various business problems like regression, Classification, prediction,  clustering and association  etc.

Machine learning (ML) is an important tool to utillise artificial intelligence technologies. Because of its learning and decision-making capabilities, machine learning is often referred to as AI, although it is actually a subdivision of AI. It was part of the development of AI until the late 1970s. Then it split off and developed independently. Machine learning has become a very important response tool for cloud computing and e-commerce.

Keywords – Sales forecasting, Machine learning, Deep neural network,  Gradient boosting, Amazon Best Sellers Rank, Forecasting, XG Boost, Gross domestic product, SHAP, Price forecasting  Price prediction, Sales prediction, Python, Jupyter