Diamond Market Insights – A Predictive Modelling Framework for Pricing Analysis

This study will create a full-scale framework for predictive modelling focused on extracting vital information regarding the market and improving price analysis for diamonds. The analysis will be based on an organized set of data comprising the globally accepted parameters for valuing diamonds, which are the 4 Cs (carat, cut, colour, and clarity), along with other characteristics such as diamond depth, table, and dimensions. The study will be conducted by applying ML algorithms for regression analysis, such as Random Forest, Gradient Boosting (XGBoost), and, if needed, Deep Learning models. The goal of the research is to find the correlation between these characteristics and predict the retail price of a diamond. One of the essential aspects of the process is to conduct proper data processing, feature engineering, and hyperparameters tuning. It will allow us to achieve accurate results that are not prone to errors in the future and have good RMSE and $R^2$ scores. This study will become a helpful instrument in making decisions and creating strategies for jewellers, valuators, and financial experts in their work with diamonds