Chapter 5 discusses the practical application of the Catboost model in
handling big data for cryptocurrency market forecasting. It details the process of model
building, from defining the problem and data collection to preprocessing, feature
selection, model selection, training, evaluation, and deployment. The chapter
emphasizes the importance of each step in transforming raw data into actionable
insights and provides a comprehensive guide on implementing Catboost models
effectively.
Keywords: Catboost, Cryptocurrency forecasting, Data preprocessing, Feature selection, Model building, Model selection, Model training, Model evaluation, Model deployment, Machine learning
