Offers a comprehensive approach to understanding and applying neural networks and deep learning models in the context of conducting economic research. By guiding readers through real-world examples, complete with Python code and access to datasets, it showcases the practical benefits of neural networks in solving complex economic problems.
Offers a comprehensive approach to understanding and applying neural networks and deep learning models in the context of conducting economic research. By guiding readers through real-world examples, complete with Python code and access to datasets, it showcases the practical benefits of neural networks in solving complex economic problems.
Andrzej Dudek is a Professor in the Department of Computer Science and Econometrics, Wroc¿aw University of Economics and Business, Wroc¿aw, Poland.
Inhaltsangabe
1. Quantitative methods in economics: Deep learning models applications 2. Deep learning model techniques 3. Regression and discrimination problems with deep neural networks 4. Explanatory model analysis for deep learning models 5. Time series analysis and forecasting with deep learning models 6. Sentiment analysis and text mining with deep learning models 7. Other applications of deep learning models Appendices
1. Quantitative methods in economics: Deep learning models applications 2. Deep learning model techniques 3. Regression and discrimination problems with deep neural networks 4. Explanatory model analysis for deep learning models 5. Time series analysis and forecasting with deep learning models 6. Sentiment analysis and text mining with deep learning models 7. Other applications of deep learning models Appendices
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