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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 2 months 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 (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-05-30T21:05:57.000Z (over 7 years ago)
- Last Synced: 2024-02-12T18:07:25.959Z (11 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
Awesome Lists containing this project
- 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 ModelsTo start learning just use the `get_tutorial` function to activate the desired tutorial:
```
library(learningAnalytics)get_tutorial("Hello")
```Enjoy!