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Preface; 1. Basic notions in classical data analysis; 2. Linear multivariate statistical analysis; 3. Basic time series analysis; 4. Feed-forward neural network models; 5. Nonlinear optimization; 6. Learning and generalization; 7. Kernel methods; 8. Nonlinear classification; 9. Nonlinear regression; 10. Nonlinear principal component analysis; 11. Nonlinear canonical correlation analysis; 12. Applications in environmental sciences; Appendix A. Sources for data and codes; Appendix B. Lagrange multipliers; Bibliography; Index.
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Add Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels, Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their application, Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels to the inventory that you are selling on WonderClubX
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Add Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels, Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their application, Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels to your collection on WonderClub |