@@ -17,6 +17,13 @@ During your work you should document it in a publicly available [white paper (or
...
@@ -17,6 +17,13 @@ During your work you should document it in a publicly available [white paper (or
After you have developed your solutions you will have the opportunity to make a short presentation about it.
After you have developed your solutions you will have the opportunity to make a short presentation about it.
**Technical infrastructure**
Especially for the event Data Science Society has provided several utilities to help you perferm and collaborate at the best of your abilities. These include:
* Gitlab setup projects (for more on gitalb read https://docs.gitlab.com/ce/gitlab-basics/README.html)
* An EC2 Amazon cloud service for each team (formore on Amazon cloud services read https://aws.amazon.com/documentation/). Don't forget that should you chose to utilize this service, you should first transfer the datasets provided with the case on the cloud instance.
* An Ubunto instance which you can use for your virtual machine on the Amazon Cloud Service with Jupyter Notebook already installed (for more on Jupyter Notebook read https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/what_is_jupyter.html). On the Notebook there are already installed all necessary kernels for data science applications (including Python, Julia, Scala, R, Octave and many more).
