Sales Forecasting using Machine Learning

This project focuses on predicting future sales using machine learning techniques. Sales forecasting helps businesses estimate future demand and make better strategic decisions. By analyzing historical sales data, machine learning models can identify patterns and generate accurate sales predictions. Project workflow included: • Data cleaning and preprocessing • Exploratory Data Analysis (EDA) • Feature engineering • Training regression models • Evaluating model performance Algorithms used include Linear Regression, Random Forest Regression, and Gradient Boosting. Technologies used in this project: Python Pandas NumPy Scikit-learn Matplotlib Seaborn This project demonstrates how machine learning can be applied to business analytics and demand forecasting.