Machine learning with R: expert techniques for predictive modeling

✍ Scribed by Lantz, Brett

Publisher: Packt Publishing
Year: 2019
Tongue: English
Edition: 3e edition
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Introducing machine learning -- Managing and understanding data -- Lazy learning : classification using nearest neighbors -- Probabilistic learning : classification using naive Bayes -- Divide and conquer : classification using decision trees and rules -- Forecasting numeric data : regression methods -- Black box methods : neural networks and support vector machines -- Finding patterns : market basket analysis using association rules -- Finding groups of data : clustering with k-means -- Evaluating model performance -- Improving model performance -- Specialized machine learning topics.

✦ Table of Contents

Introducing machine learning --
Managing and understanding data --
Lazy learning : classification using nearest neighbors --
Probabilistic learning : classification using naive Bayes --
Divide and conquer : classification using decision trees and rules --
Forecasting numeric data : regression methods --
Black box methods : neural networks and support vector machines --
Finding patterns : market basket analysis using association rules --
Finding groups of data : clustering with k-means --
Evaluating model performance --
Improving model performance --
Specialized machine learning topics.

✦ Subjects

Datenaustausch;Machine learning / Statistical methods;Machine learning / Statistical methods / Handbooks, manuals, etc;Maschinelles Lernen;R (Computer program language);R (Computer program language) / Handbooks, manuals, etc;R (Programm);Statistik

📜 SIMILAR VOLUMES

Machine Learning with R: Expert techniqu

📁 Machine Learning with R: Expert techniques for predictive modeling

✍ Brett Lantz 📂 Library 📅 2019 🏛 Packt Publishing Limited 🌐 English

Solve real-world data problems with R and machine learning Key Features Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.5 and beyond Harness the power of R to build flexible, effective, and transparent machine learning models Learn quick

Machine Learning with R: Expert techniqu

📁 Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition

✍ Brett Lantz 📂 Library 📅 2019 🏛 Packt Publishing 🌐 English

<p><b>Solve real-world data problems with R and machine learning</b></p> <h4>Key Features</h4> <ul><li>Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.6 and beyond </li> <li>Harness the power of R to build flexible, effective, and transparent

Machine Learning with R: Expert Techniqu

📁 Machine Learning with R: Expert Techniques for Predictive Modeling to Solve All Your Data Analysis Problems

✍ Brett Lantz 📂 Library 📅 2015 🏛 Packt Publishing 🌐 English

<h4>Key Features</h4><ul><li>Harness the power of R for statistical computing and data science</li><li>Explore, forecast, and classify data with R</li><li>Use R to apply common machine learning algorithms to real-world scenarios</li></ul><h4>Book Description</h4><p>Machine learning, at its core, is

Machine Learning for Knowledge Discovery

📁 Machine Learning for Knowledge Discovery with R: Methodologies for Modeling, Inference and Prediction

✍ Kao-Tai Tsai 📂 Library 📅 2021 🏛 Chapman and Hall/CRC 🌐 English

<p><strong>Machine Learning for Knowledge Discovery with R</strong> contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as recursive partitioning modelling,

Statistics for Machine Learning: Techniq

📁 Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

✍ Pratap Dangeti 📂 Library 📅 2017 🏛 Packt Publishing 🌐 English

<h4>Key Features</h4><ul><li>Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics.</li><li>Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering.</li><li>Master the statistical aspect of

Statistics for Machine Learning: Techniq

📁 Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

✍ Pratap Dangeti 📂 Library 📅 2017 🏛 Packt Publishing 🌐 English