https://bradleyboehmke.github.io/learningAnalytics/

An R package that provides a structured learning environment to deliver tutorials covering various statistical learning techniques
https://bradleyboehmke.github.io/learningAnalytics/

data-science education r statistical-learning teaching

Last synced: about 1 month ago
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An R package that provides a structured learning environment to deliver tutorials covering various statistical learning techniques

• Host: GitHub
• URL: https://bradleyboehmke.github.io/learningAnalytics/
• Owner: bradleyboehmke
• Created: 2017-05-09T15:20:26.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2017-05-30T21:05:57.000Z (about 7 years ago)
• Last Synced: 2024-02-12T18:07:25.959Z (5 months ago)
• Topics: data-science, education, r, statistical-learning, teaching
• Language: HTML
• Homepage: https://bradleyboehmke.github.io/learningAnalytics/
• Size: 7.51 MB
• Stars: 3
• Watchers: 3
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd

Lists

• awesome-LearnRwithR - learningAnalytics - Tutorials covering various statistical techniques by *Brad Boehmke*. (Content / Tutorials Guides & Courses)

README

        
---

output: github_document

---

```{r, echo = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "README-"

)

```

# learningAnalytics

 

**Author:** [Brad Boehmke](http://bradleyboehmke.github.io/)


**License:** [GPL (>= 2)](https://opensource.org/licenses/gpl-license)

`learningAnalytics` is an R package that provides a structured learning environment to deliver tutorials covering various statistical learning techniques.

## Installation

You can install `learningAnalytics` straight from GitHub with:

```

if (packageVersion("devtools") < 1.6) {

  install.packages("devtools")

}

devtools::install_github("bradleyboehmke/learningAnalytics")

```

## Start Learning

`learningAnalytics` provides several tutorials covering common analytic techniques:

1. "Hello": An introduction to `learningAnalytics`

2. "EDA": Exploratory Data Analysis

3. "Unsupervised": Principal Components Analysis & Cluster Analysis

4. "Linear Regression": Linear Regression

5. "Supervised Classification": Logistic Regression & Discriminant Analysis

6. "Resampling": Leave-One-Out Cross-Validation, *k*-Fold Cross Validation, & Bootstrapping

7. "Model Selection": Best Subset & Stepwise Selection for Linear Models

To start learning just use the `get_tutorial` function to activate the desired tutorial:

```

library(learningAnalytics)

get_tutorial("Hello")

```

Enjoy!