Instacart-Predictive-MBA-Analysis
Part 1: Understanding the dataset. Data Cleaning: Techniques like data imputation, adjusting discrepancies and data normalization. Data Exploration and Descriptive analysis of data: Achieved by using data visualizations. Extraction of important characteristics from dataset for further analysis.
Part 2: Feature Engineering (Construction of dataset features from selected columns). Modeling and Prediction (Models like XGBoost, Random Forest, Decision Trees). Market Basket Analysis. Business Implications based on Modeling and Market Basket Analysis.
Project Deliverables: Customer Retention. New Customers Attraction. Customer Experience Enhancement. Instacart Profitable Collaborative Partners. Inventory Management.