diff --git a/README.md b/README.md index ce0b254..b4c8c44 100644 --- a/README.md +++ b/README.md @@ -92,6 +92,18 @@ Python is by far the most popular language in science, due in no small part to t Unlike R, Python was not built from the ground up with data science in mind, but there are plenty of third party libraries to make up for this. A much more exhaustive list of packages can be found later in this document, but these four packages are a good set of choices to start your data science journey with: [Scikit-Learn](https://scikit-learn.org/stable/index.html) is a general-purpose data science package which implements the most popular algorithms - it also includes rich documentation, tutorials, and examples of the models it implements. Even if you prefer to write your own implementations, Scikit-Learn is a valuable reference to the nuts-and-bolts behind many of the common algorithms you'll find. With [Pandas](https://pandas.pydata.org/), one can collect and analyze their data into a convenient table format. [Numpy](https://numpy.org/) provides very fast tooling for mathematical operations, with a focus on vectors and matrices. [Seaborn](https://seaborn.pydata.org/), itself based on the [Matplotlib](https://matplotlib.org/) package, is a quick way to generate beautiful visualizations of your data, with many good defaults available out of the box, as well as a gallery showing how to produce many common visualizations of your data. When embarking on your journey to becoming a data scientist, the choice of language isn't particularly important, and both Python and R have their pros and cons. Pick a language you like, and check out one of the [Free courses](#free-courses) we've listed below! + +## Real World +**[`^ back to top ^`](#awesome-data-science)** + +Data science is a powerful tool that is utilized in various fields to solve real-world problems by extracting insights and patterns from complex data. + +### Disaster +**[`^ back to top ^`](#awesome-data-science)** + +- [deprem-ml](https://huggingface.co/deprem-ml) [AYA: Açık Yazılım Ağı](https://linktr.ee/acikyazilimagi) (+25k developers) is trying to help disaster response using artificial intelligence. Everything is open-sourced [afet.org](https://afet.org). + + ## Training Resources **[`^ back to top ^`](#awesome-data-science)** @@ -172,6 +184,7 @@ How do you learn data science? By doing data science, of course! Okay, okay - th - [Data Scientist with Python](https://app.datacamp.com/learn/career-tracks/data-scientist-with-python) + ### Intensive Programs **[`^ back to top ^`](#awesome-data-science)**