In the field of data processing and analytics, machine learning has emerged as a topic of significant interest in the recent years. When it comes to decision-making, less structured retailers rely on their gut feeling, whereas more structured retailers make use of business intelligence. Predicting future retail sales is a common practise in the industry of organised retail, where it is tremendously helpful for making timely and strategic decisions in the face of intense competition. Predictions about future sales are often arrived at by doing an analysis of previous data, making use of a variety of statistical and mathematical methodologies, etc. This study is an endeavour to communicate with retail business owners, managers, and policymakers the accuracy of data derived from retail sales forecasting using machine learning algorithms. In this study, we apply the machine learning techniques known as Artificial Neural Network and Random Forest to a dataset that is often used for training purposes.
關聯:
Advancements in Science and Technology for Healthcare, Agriculture, and Environmental Sustainability 1st edition
