📊 CPI Inflation Analysis & Prediction (Machine Learning)

📌 Project Overview

This project analyzes global Consumer Price Index (CPI) data and predicts inflation using Machine Learning techniques.

🎯 Objectives

• Analyze global inflation trends
• Perform exploratory data analysis (EDA)
• Detect outliers and correlations
• Build prediction model using Linear Regression

📂 Dataset

• Source: IMF CPI Dataset
• Time Period: April 2025 – March 2026
• Features: Monthly CPI values, country, category (COICOP)

⚙️ Technologies Used

• Python
• Pandas, NumPy
• Matplotlib, Seaborn
• Scikit-learn

📊 Key Analysis

• Descriptive Statistics
• Correlation Heatmap
• Pairplot Analysis
• Outlier Detection
• Country-wise and Category-wise Trends

🤖 Machine Learning Model

• Linear Regression (OLS)

📈 Model Performance

• MAE: ~0.58
• RMSE: ~1.12
• R² Score: 0.95

🔍 Key Insights

• High inflation concentrated in few countries
• Strong correlation between monthly CPI values
• 6-month data sufficient for prediction
• Food, Energy, Housing drive inflation

📁 Project Structure