Data Science For Mathematicians

Learn Advanced Data Visualization with Python 3, NumPy, Jupyter, Matplotlib, Pandas, Seaborn, and Bokeh

The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining. Bayesian methods play a role central to the future of data and knowledge integration in the field of Bioinformatics. This book is devoted exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing Bioinformatics. Case studies, illustrating Bayesian analyses of public gene expression data, provide the backdrop for students to develop analytical skills, while the more experienced readers will find the review of advanced methods challenging and attainable.

Take your visualizations beyond boring charts.

Using a 7-Step Procedure, learn how calculate and validate the Mahalanobis Distance Test

Using a 7-Step Procedure, learn how calculate and validate the Mahalanobis Distance Test

Build a Foundation for Your Career in IT. Master the math powering our lives and prepare for your software engineer or security analyst career.

This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical linear algebra topics and numerical solution methods, which are relevant for problems arising in statistics and in big data. The contributions were originally presented at the 25th International Workshop on Matrices and Statistics (IWMS 2016), held in Funchal (Madeira), Portugal on June 6-9, 2016.