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https://github.com/jhermann/til-about-data-science

:mortar_board: :panda_face: Records of what I learned while exploring the waters of Data Science (using Python)
https://github.com/jhermann/til-about-data-science

artificial-intelligence data-science know-how machine-learning matplotlib pandas python seaborn today-i-learned visualization

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:mortar_board: :panda_face: Records of what I learned while exploring the waters of Data Science (using Python)

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README

        

# Today I Learned about Data Science…

> Records of what I learned while exploring the waters of *data science* (using *Python*).

**Contents**

* [What is this about?](#what-is-this-about)
* [How can I use it?](#how-can-i-use-it)
* [Legal Stuff](#legal-stuff)

## What is this about?

This repository is first and foremost a reference for myself on what I learned
foraying into anything data science. Still, and that is part of making it public,
I hope that others can benefit from those insights and examples.

Note that I'm somewhat versed in programming and computer stuff, so coming into
data science I'm sort of an experienced novice. :wink:

My challenges might not be yours, and likely I'm puzzled by different things than you.
However, if you find yourself in a place where as an IT professional you want to learn about data science,
then chances are very high you can profit from this.

See also [jupyter-by-example](https://github.com/jhermann/jupyter-by-example).

## How can I use it?

Explanations and other prose that is not part of a
[Jupyter Notebook](https://github.com/jhermann/til-about-data-science/tree/master/jupyter#jupyter-notebooks)
can be found in the
[wiki](https://github.com/jhermann/til-about-data-science/wiki).
Specifically, *links to outside sources* like blog posts, online courses, videos etc. are placed there.

The wiki also provides a guided tour on data science topics in general,
as well as notebooks, code and such contained in the repository itself.

## Legal Stuff

Code in this repository is [MIT licensed](https://github.com/jhermann/til-about-data-science/blob/master/LICENSE),
while the wiki is [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).

While on the topic of legislation:
[Fight for your rights as a digital native, against the 20th century trolls](https://www.linuxjournal.com/content/how-eus-copyright-reform-threatens-open-source-and-how-fight-it)!