Data Analysis

Introduction – Describe the dataset and project objective.

Data Cleaning – Show how you handled missing values and irrelevant columns.

Exploratory Data Analysis – Optional plots (limit < 5 figures).

Model Building – Describe Random Forest choice and hyperparameters.

Cross-validation & Accuracy – Report confusion matrix and expected out-of-sample error.

Predictions – Show test set predictions.

Conclusion – Summarize results and why you chose your approach.