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Description of  Fundamentals of Data Analytics: With a View to Machine Learning

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. i will be very grateful when you support me and buy Or Renew Your Premium from my i appreciate your support Too much as it will help me to post more and more Without You And Your Support We Cant Continue Thanks For Buying Premium From My Links For Support