# Framework(s) / checklist(s)

- [Data Science Primer](https://elitedatascience.com/primer)
- [How to Prepare Data For Machine Learning](https://machinelearningmastery.com/how-to-prepare-data-for-machine-learning/)
- [What is Data Mining and KDD](https://machinelearningmastery.com/what-is-data-mining-and-kdd/)
- [The KDD process for extracting useful knowledge from volumes of data](http://shawndra.pbworks.com/f/The%20KDD%20process%20for%20extracting%20useful%20knowledge%20from%20volumes%20of%20data.pdf)
- [Data Mining: Practical ML Tools and Techniques by Witten, Frank and Mark 3rd edition](https://www.wi.hs-wismar.de/~cleve/vorl/projects/dm/ss13/HierarClustern/Literatur/WittenFrank-DM-3rd.pdf)
- [Foundational Methodology for Data Science - IBM Analytics Whitepaper](https://tdwi.org/~/media/64511A895D86457E964174EDC5C4C7B1.PDF)
- See [Courses](../courses.md#courses)

# Contributing

Contributions are very welcome, please share back with the wider community (and get credited for it)!

Please have a look at the [CONTRIBUTING](../CONTRIBUTING.md) guidelines, also have a read about our [licensing](../LICENSE.md) policy.

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