Predict construction project costs using Machine Learning. Use Linear Regression, K-Nearest Neighbors, and Random Forest models on historical project data. Train, evaluate, and deploy cost prediction models.
Major update: Adds comprehensive guidance and code for construction cost prediction using multiple ML models. - Introduces an in-depth SKILL.md with project overview, methodology, and book reference. - Provides detailed code snippets for data preparation, feature engineering, and handling inflation adjustments. - Offers step-by-step instructions for training and evaluating Linear Regression, K-Nearest Neighbors, Random Forest, and Gradient Boosting models. - Includes model evaluation metrics (MAE, RMSE, R², MAPE) and feature importance analysis. - Enables easy model comparison for optimal selection.