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Statistical Learning and Modeling in Data Analysis

The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series;

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Statistical Modeling in Biomedical Research

and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their;

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Statistical Modeling in Biomedical Research: Contemporary Topics and Voices in the Field

and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications;

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Advances in Intelligent Data Analysis XIX

networks; modeling with statistical learning; modeling language and graphs; and modeling special data formats.;

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Training Systems Using Python Statistical Modeling

it to become the choice of tool for many data scientists and machine learning developers today. Its rich libraries are widely used for data;

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Multiscale Signal Analysis and Modeling

Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This;

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Bayesian Modeling in Bioinformatics

Bayesian kernel machines, and QTL mapping. Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume;

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Bayesian Modeling in Bioinformatics

Bayesian kernel machines, and QTL mapping. Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume;

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Applied Statistical Modeling and Data Analytics

Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciencesprovides a practical guide to many;

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Statistics, Data Analysis And Decision Modeling

: statistical thinking in business; displaying and summarizing data; random variables; sampling; regression analysis; forecasting; statistical quality;

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Statistical Application Development with R and Python -

preliminary concepts right away using R and Python. * Understand data modeling and visualization to perform efficient statistical analysis with this;

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Reliability and Statistical Computing

maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep;

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Reliability and Statistical Computing

maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep;

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Advanced R Statistical Programming and Data Models

data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R;

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Pricing Analytics

, discrete choice, MaxDiff) and sales data modeling. Experimental design principles, model estimation approaches, and analysis methods are discussed;

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Pricing Analytics

from data. Specifically, itcomes from statistically modeling the data. This book gives the reader the statistical modeling tools needed to;

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Statistical and Machine Learning Approaches for Network Analysis

weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross;

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Introduction to Multivariate Analysis

of both traditional and newer techniques in multivariate analysis and machine learning. It also introduces linear and nonlinear statistical;

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Introduction to Multivariate Analysis

traditional and newer techniques in multivariate analysis and machine learning. It also introduces linear and nonlinear statistical modeling for;

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Statistical Learning and Data Sciences

This book constitutes the refereed proceedings of the Third International Symposium on Statistical Learning and Data Sciences, SLDS 2015;

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Machine Learning for Vision-Based Motion Analysis: Theory and Techniques

application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions;

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Machine Learning for Knowledge Discovery with R

of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as recursive partitioning modelling;

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Time Series Algorithms Recipes

-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical;

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Statistical Analysis of Network Data with R

The new edition of this book provides an easily accessible introduction to the statistical analysis of network data using R. It has been;

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Machine Learning in Medicine

Machine learning is concerned with the analysis of large data and multiple variables. It is also often more sensitive than traditional;

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Statistical Modeling and Machine Learning for Molecular Biology

Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The;

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Statistical Modeling and Machine Learning for Molecular Biology

Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The;

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