https://github.com/clarelgibson/machine-learning-specialization-r
Includes worked examples in R of the machine learning algorithms covered in the Stanford/DeepLearning Machine Learning Specialisation
https://github.com/clarelgibson/machine-learning-specialization-r
classification-algorithms linear-regression logistic-regression machine-learning r r-language
Last synced: 2 months ago
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Includes worked examples in R of the machine learning algorithms covered in the Stanford/DeepLearning Machine Learning Specialisation
- Host: GitHub
- URL: https://github.com/clarelgibson/machine-learning-specialization-r
- Owner: clarelgibson
- License: cc0-1.0
- Created: 2025-03-05T17:34:41.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2025-03-05T17:43:56.000Z (2 months ago)
- Last Synced: 2025-03-05T18:42:37.870Z (2 months ago)
- Topics: classification-algorithms, linear-regression, logistic-regression, machine-learning, r, r-language
- Homepage:
- Size: 4.88 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Machine Learning in R
This repository contains worked examples in R of the machine learning algorithms covered in Andrew Ng's [Machine Learning Specialization](https://www.coursera.org/specializations/machine-learning-introduction) available on [Coursera](https://www.coursera.org).
## Description
In February 2025 I enrolled into the Machine Learning Specialization on Coursera. The course is jointly offered by [Stanford](https://www.coursera.org/partners/stanford) and [DeepLearning.ai](https://www.coursera.org/partners/deeplearning-ai) and the principal instructor is Stanford professor [Andrew Ng](https://en.wikipedia.org/wiki/Andrew_Ng). It is a great introduction to some of the most commonly used machine learning algorithms. In order for me to fully understand all of the concepts taught in the course, I felt that I needed to work through my own examples. While the course is taught using python, I chose to use R for this exercise, both because it's a language I am more familiar with and because it forces me to think and write the code for myself, rather than copy the code used in the lectures.
## Algorithms
- [Linear regression](R/linear-regression.md)
## Author
- [Clare Gibson](https://www.datatranslator.co.uk)
## Licence
This project is licensed under the CC0 1.0 Universal licence. See the [LICENSE](./LICENSE) file for details.
## Acknowledgements
- [Machine Learning Specialization](https://www.coursera.org/specializations/machine-learning-introduction)
- [Coursera](https://coursera.org)
- [DeepLearning.ai](https://deeplearning.ai)