https://github.com/tawfikhammad/data-rescaling-and-normalization
data rescaling, normalization and standardization techniques
https://github.com/tawfikhammad/data-rescaling-and-normalization
data-cleaning data-normalization data-scaling data-standardization machine-learning
Last synced: 6 months ago
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data rescaling, normalization and standardization techniques
- Host: GitHub
- URL: https://github.com/tawfikhammad/data-rescaling-and-normalization
- Owner: tawfikhammad
- License: mit
- Created: 2023-09-23T18:14:26.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-12-02T13:13:14.000Z (about 2 years ago)
- Last Synced: 2023-12-02T14:26:00.976Z (about 2 years ago)
- Topics: data-cleaning, data-normalization, data-scaling, data-standardization, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 841 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# data-rescaling-and-normalization
It's easy to get confused between scaling and normalization is because the terms are sometimes used interchangeably and they are very similar! In both cases, you're transforming the values of numeric variables so that the transformed data points have specific helpful properties. The difference is that:
* [scaling](https://github.com/tawfikhammad/data-rescaling-and-normalization/tree/main/Scaling) : you're changing the range of your data.
* [normalization](https://github.com/tawfikhammad/data-rescaling-and-normalization/tree/main/normalization) : you're changing the shape of the distribution to normal distributed.
* [standardization(Z-score)](https://github.com/tawfikhammad/data-rescaling-and-normalization/tree/main/standardization) : changing the shape of the distribution to standard normal distributed.
## License
The code and models in this repository are available under the [MIT License](./LICENSE). Feel free to use them for academic, research, or commercial purposes.