Dataset and Preprocessing:

• The dataset used in the project contained information about retail sales, including features such as quantity, price, and customer demographics.

• Data preprocessing tasks were performed to ensure the quality and usability of the dataset.

• Steps such as handling missing values, encoding categorical variables, and scaling numerical features were implemented.

• Exploratory data analysis (EDA) techniques were applied to gain insights into the dataset, identify outliers, and understand the distribution of variables.