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A Computational Approach to Statistical Learning

A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and;

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A Computational Approach to Statistical Learning

A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and;

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Computational Statistics

Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional;

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Computational Statistics

Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional;

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Computational Biology

Ground Computational Biology: A Statistical Mechanics Perspective is the first book dedicated to the interface between statistical physics and;

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Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis;

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Statistical Computing with R

Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve;

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Handbook of Computational Social Science - Vol 1 & Vol 2

debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the;

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Applications in Statistical Computing

on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book;

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Computational and Statistical Methods for Protein Quantification by Mass Spectrometry

spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of quantitative;

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Statistical Modeling and Machine Learning for Molecular Biology

book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big;

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Statistical Modeling and Machine Learning for Molecular Biology

book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big;

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An Introduction to Computational Learning Theory

. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the;

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Semisupervised Learning for Computational Linguistics

. Taking an intuitive approach to the material, this lucid book facilitates the application of semisupervised learning methods to natural language;

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Semisupervised Learning for Computational Linguistics

. Taking an intuitive approach to the material, this lucid book facilitates the application of semisupervised learning methods to natural language;

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Computational Analysis of Communication

science, sociology, psychology, and media studies, the use of computational analysis is rapidly increasing. Statistical modeling, machine learning;

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Computational Intelligence Techniques for Comparative Genomics

statistical analysis approach to effectively study the disorders and possible causes along with medical applications.;

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Computational Neuroscience for Advancing Artificial Intelligence

lies in its theoretical advances, which are grounded in an understanding of computational and biological learning. The approach taken moves the;

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Using R for Introductory Statistics

, owing to its coherence, flexibility, and free availability. While it is a valuable tool for students who are first learning statistics, proper;

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Molecular Evolution

interpretation. Molecular Evolution: a statistical approach presents and explains modern statistical methods and computational algorithms for the;

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Introductory Organic Chemistry and Hydrocarbons

statistical thermodynamic concepts aiming to enrich the learning process of the organic molecular properties and organic reactions. A detailed;

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Introductory Organic Chemistry and Hydrocarbons

statistical thermodynamic concepts aiming to enrich the learning process of the organic molecular properties and organic reactions. A detailed;

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Computational Reconstruction of Missing Data in Biological Research

data. In this book, we introduce different types of biological data missing scenarios and propose machine learning models to improve the data;

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Statistical Computing with R, Second Edition

in computational statistics or for self-study, Statistical Computing with R, Second Edition provides a balanced, accessible introduction to computational;

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Introduction to Probability and Statistics Metric Edition

intimidating course, but this text reinforces a common-sense approach to statistical descriptions and procedures and equips you with a firm foundation;

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Machine Learning Research Progress

automatically, by computational and statistical methods. Hence, machine learning is closely related not only to data mining and statistics, but also;

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Data Science in R

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation Data Science in R: A Case Studies Approach to;

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