Last updated: 2025-02-18

Checks: 2 0

Knit directory: Tutorials/

This reproducible R Markdown analysis was created with workflowr (version 1.7.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Repository version: 397f9b2

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version 397f9b2. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated: 


Ignored files:
    Ignored:    .DS_Store
    Ignored:    .RData
    Ignored:    .Rhistory
    Ignored:    data/.DS_Store

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/index.Rmd) and HTML (docs/index.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
html 5baa04e tkcaccia 2025-02-17 Build site.
html f26aafb tkcaccia 2025-02-17 Build site.
html 1ce3cb4 tkcaccia 2025-02-16 Build site.
html 681ec51 tkcaccia 2025-02-16 Build site.
html 9558051 tkcaccia 2024-09-18 update
html a7f82c5 tkcaccia 2024-09-18 Build site.
html 83f8d4e tkcaccia 2024-09-16 Build site.
html 159190a tkcaccia 2024-09-16 Build site.
html 6d23cdb tkcaccia 2024-09-16 Build site.
html 6301d0a tkcaccia 2024-09-16 Build site.
html 897778a tkcaccia 2024-09-16 Build site.
html 1a34734 tkcaccia 2024-09-16 Build site.
html 5033c12 tkcaccia 2024-09-16 Build site.
Rmd 15be19f tkcaccia 2024-09-16 Start workflowr project.
html e54f6b5 tkcaccia 2024-09-05 Build site.
Rmd 8486be7 tkcaccia 2024-09-05 update
html ba4d473 GitHub 2024-09-05 Create index.html

This site is designed to provide you with valuable insights and hands-on experience through a series of detailed modules. Each module covers a different aspect of data science, from foundational concepts to advanced techniques.

Discover unsupervised learning methods. This module focuses on techniques for identifying patterns and structures in unlabeled data, including clustering and dimensionality reduction.

Feel free to navigate through the modules using the links above to gain a deeper understanding of each topic. Whether you’re new to data science or looking to refine your skills, this site offers a wealth of information and practical exercises to enhance your knowledge.