Andere Kunden interessierten sich auch für
![Statistical Inference and Machine Learning for Big Data]( "Statistical Inference and Machine Learning for Big Data")
Statistical Inference and Machine Learning for Big Data103,99 €![Machine Learning and Big Data Analytics]( "Machine Learning and Big Data Analytics")
Machine Learning and Big Data Analytics132,99 €![A Parametric Approach to Nonparametric Statistics]( "A Parametric Approach to Nonparametric Statistics")
A Parametric Approach to Nonparametric Statistics37,99 €![A Parametric Approach to Nonparametric Statistics]( "A Parametric Approach to Nonparametric Statistics")
A Parametric Approach to Nonparametric Statistics52,99 €![Contemporary Experimental Design, Multivariate Analysis and Data Mining]( "Contemporary Experimental Design, Multivariate Analysis and Data Mining")
Contemporary Experimental Design, Multivariate Analysis and Data Mining125,99 €![Contemporary Experimental Design, Multivariate Analysis and Data Mining]( "Contemporary Experimental Design, Multivariate Analysis and Data Mining")
Contemporary Experimental Design, Multivariate Analysis and Data Mining125,99 €![Mathematical Foundations for Data Analysis]( "Mathematical Foundations for Data Analysis")
Mathematical Foundations for Data Analysis41,99 €
This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life applications in a variety of areas such as genetics, medicine, and environmental problems.
The book begins in Part I by outlining various data types and by indicating how these are normally represented graphically and subsequently analyzed. In Part II, the basic tools in probability and statistics are introduced with special reference to symbolic data analysis. The most useful and relevant results pertinent to this book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented.
This book would serve as a handy desk reference for statistical methods at the undergraduate and graduate level as well as be useful in courses which aim to provide an overview of modern statistics and its applications.
The book begins in Part I by outlining various data types and by indicating how these are normally represented graphically and subsequently analyzed. In Part II, the basic tools in probability and statistics are introduced with special reference to symbolic data analysis. The most useful and relevant results pertinent to this book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented.
This book would serve as a handy desk reference for statistical methods at the undergraduate and graduate level as well as be useful in courses which aim to provide an overview of modern statistics and its applications.