ai budget tracker

AI Financial Coach: Budget & Savings Predictor Project Overview This project implements a next-generation personal finance application that transforms historical transaction data into proactive, personalized financial advice using a continuous four-step AI/ML cycle: Collect, Analyze, Predict, and Recommend (CAPR). The goal is to provide users with a "Financial Co-pilot" that helps them achieve specific savings goals and avoid unexpected budget shortfalls. 1. The AI Cycle Architecture (CAPR) Phase Description Key Metric / Output Underlying Technology (Simulated) Collect Data Ingestion & Cleaning: Securely import or manually input all user transactions (income, expenses, transfers). Cleaned, normalized data set; 98% Auto-Categorization Rate Python (Pandas), NLP for transaction description clustering (e.g., using simulated scikit-learn text embeddings). Analyze Descriptive Analytics: Understand current spending habits, identify trends, fixed/variable costs, an