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XploRe - Learning Guide

guide is intended for beginners in computer-aided statistical data analysis. The prerequisites for XploRe - the statistical computing;

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An Introduction to Statistical Learning

cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge;

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An Introduction to Statistical Learning

cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge;

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Statistical Learning from a Regression Perspective

data analytics, it emphasizes that a proper statistical learning data analysis depends in an integrated fashion on sound data collection;

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Machine Learning for Knowledge Discovery with R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction;

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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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Elements Of Statistical Learning Data

framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use;

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Computational Learning Approaches to Data Analytics in Biomedical Applications

using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms;

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Statistical Data Analytics

informatics and data analytics to practitioners who regularly apply statistical learning to their modern data.;

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Data Analysis with IBM SPSS Statistics

to perform efficient statistical analysis of your data * Choose the right statistical technique to analyze different types of data and build;

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Classification, (Big) Data Analysis and Statistical Learning

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data;

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Statistical Learning Theory

A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem;

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Boosted Statistical Relational Learners

This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational;

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Practical Statistics for Data Scientists

belongs to Statistical machine learning methods that learn from data Unsupervised learning methods for extracting meaning from unlabeled data;

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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 Learning and Data Science

new heights of achievement in the incredibly rich data world that we inhabit. Statistical Learning and Data Science is a work;

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Statistical Learning and Data Science

new heights of achievement in the incredibly rich data world that we inhabit. Statistical Learning and Data Science is a work;

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Knowledge Discovery with Support Vector Machines

of machine learning and goes on to cover: Knowledge discovery environments Describing data mathematically Linear decision surfaces and functions;

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Python Machine Learning

practices to improve and optimize machine learning systems and algorithms * Ask - and answer - tough questions of your data with robust statistical;

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Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies

research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal;

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Statistical Reinforcement Learning

field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms;

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Statistical Reinforcement Learning

field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms;

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Survival Analysis for Epidemiologic and Medical Research

data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key;

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Statistical Quality Control - Using MINITAB, R, JMP and Python

data encountered in real life situations to support each theoretical concept. Statistical Quality Control: Using MINITAB, R, JMP and Python;

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Statistical and Machine Learning Approaches for Network Analysis

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches;

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Statistics and Machine Learning Methods for EHR Data

The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning;

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Mathematical Problems in Data Science

of data science problems including machine learning methods, mathematical image and video processing, topological data analysis, and statistical;

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