This project is a machine learning–based web application that predicts house prices using historical real estate data. The model considers multiple factors such as house size, location, condition, and ...
This project implements a simplified GPT-2 style Transformer (2-4 layers, 128 hidden dimensions) trained on tokenized K-line data to predict price movements. The model processes 500 historical K-lines ...
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