This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
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Idioma Inglés ● Formato EPUB ● ISBN 9783030568313 ● Editorial Springer International Publishing ● Publicado 2020 ● Descargable 3 veces ● Divisa EUR ● ID 8148343 ● Protección de copia Adobe DRM
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