Sales Prediction and Customer Insights Analysis

Objective: Develop a predictive model to analyze customer behavior and enhance sales forecasting by leveraging historical transaction data stored in SQL databases.

Data Collection & Preparation: Extract and preprocess data using SQL queries, ensuring data quality and feature engineering, followed by using Python libraries (like Pandas and NumPy) for data manipulation.

Model Development & Evaluation: Implement machine learning algorithms (e.g., regression, classification) using Python's scikit-learn, and evaluate model performance with metrics like accuracy and F1-score, ultimately aiming to deliver actionable insights for strategic decision-making.