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These notebooks provide a comprehensive workflow, from start to finish, for processing and analyzing the SWAN-SF dataset. They include detailed steps for reading the dataset files, performing full preprocessing, and executing classification.
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House price prediction involves analyzing data points to estimate the value of a residential property using statistical techniques such as regression analysis and machine learning algorithms. It is useful for both buyers and sellers in making informed decisions based on market trends and property values.