Learning RStudio for R statistical computing : learn to effectively perform R development, statistical analysis, and reporting with the most popular R IDE

Learning RStudio for R statistical computing : learn to effectively perform R development, statistical analysis, and reporting with the most popular R IDE

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Xehetasun bibliografikoak
Egile nagusia:	Van der Loo, Mark P.J.. (Egilea)
Beste egile batzuk:	De Jonge, Edwin. (Auteur)
Formatua:	E-Book
Hizkuntza:	Anglais
Argitaratua:	Birmingham : Packt Publishing, 2012.
Gaiak:	RStudio > logiciel.
Autres localisations:	Voir dans le Sudoc
Sarrera elektronikoa:	Accès à l'E-book

Antzeko izenburuak

RStudio for R statistical computing cookbook
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Argitaratua: (2016)

Statistical analysis with R for dummies
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Introduction to statistical machine learning
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Argitaratua: (2015)

Applied statistics for environmental science with R
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Argitaratua: (2019)

Basic statistics with R : reaching decisions with data
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Argitaratua: (2021)

Mastering machine learning with R
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Argitaratua: (2017)

Statistics, Data Mining, and Machine Learning in Astronomy : A Practical Python Guide for the Analysis of Survey Data
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Argitaratua: (2019)

R machine learning by example : understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully
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Argitaratua: (2016)

Practical machine learning in R
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Probability and Statistics
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Argitaratua: (2005)

Learning Bayesian models with R : become an expert in Bayesian machine learning methods using R and apply them to solve real-world big data problems
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Argitaratua: (2015)

R deep learning cookbook : solve complex neural net problems with TensorFlow, H2O and MXNet
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Argitaratua: (2017)

MATLAB for machine learning
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The rise of statistical thinking : 1820-1900
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Argitaratua: (2020)

Statistical mechanics
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Argitaratua: (2011)

Robust Statistics : Theory and Methods
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Argitaratua: (2006)

Probability, statistics, and stochastic processes
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Moodle for mobile learning : connect, communicate, and promote collaboration with your coursework using Moodle
nork: Aberdour, Mark.
Argitaratua: (2013)

Machine learning avec Scikit-Learn : mise en oeuvre et cas concrets
nork: Géron, Aurélien (19..-....).

Methods and applications of statistics in clinical trials.
nork: Balakrishnan, Narayanaswamy (1956-....).
Argitaratua: (2014)

Statistics for big data for dummies.
Argitaratua: (2015)

Learning IPython for interactive computing and data visualization
nork: Rossant, Cyrille (1985-....).
Argitaratua: (2015)

Machine learning for developers : uplift your regular applications with the power of statistics, analytics, and machine learning
nork: Bonnin, Rodolfo.
Argitaratua: (2017)

Introduction to Statistical Physics
nork: Huang, Kerson (1928-2016).
Argitaratua: (2001)

Learning QGIS 2.0 : use QGIS to create maps and perform all the geoprocessing tasks you need
nork: Graser, Anita.
Argitaratua: (2013)

Learning Vue.js 2 : learn how to build amazing and complex reactive web applications easily with Vue.js
nork: Filipova, Olga.
Argitaratua: (2016)

OpenNebula 3 cloud computing : set up, manage, and maintain your cloud and learn solutions for datacenter virtualization with this step-by-step practical guide
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Argitaratua: (2012)

Data mining and statistics for decision making
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Argitaratua: (2011)

Learning Julia : build high-performance applications for scientiﬁc computing
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Argitaratua: (2017)

OpenStack Cloud Computing Cookbook
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Machine Learning Algorithms : Reference guide for popular algorithms for data science and machine learning
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Mathematica Data Analysis : learn and explore the fundamentals of data anlysis with the power of Mathematica
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Argitaratua: (2015)

OpenCV computer vision application programming cookbook : recipes to help your build computer vision applications that make the most of the popular C++ library OpenCV 3
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Séries temporelles avec R
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Réseaux bayésiens avec R
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Mastering RStudio : develop, communicate, and collaborate with R
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R pour les scientifiques : mise en oeuvre de projets et valorisation des résultats
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Analyse factorielle multiple avec R
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Argitaratua: (2013)

Machine learning for time series forecasting with Python
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Computational Thinking
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