Explainable Data Science Course

5/3/2020 Download:Explainable Data Science

ExplainableDataScience Repository

This repository contains notebooks used in the Explainable Data Science Course.

Course Description

Explainability is one of the most important problems of machine learning and a hot topic in both academia and industry. This course will cover the basics of explainability.

Course Instructor

Jordi Vitrià, Universitat de Barcelona

Course Software Installation

You can develop machine learning applications with Google Colaboratory (Colab). Colab is a Google internal research tool for data science. They have released the tool to the general public with the goal of dissemination of machine learning education and research.

You can find more information in this blogs:

• https://medium.com/deep-learning-turkey/google-colab-free-gpu-tutorial-e113627b9f5d
• https://medium.com/tensorflow/colab-an-easy-way-to-learn-and-use-tensorflow-d74d1686e309

Follow these steps in order to work in Colab:

• Connect to https://colab.research.google.com/ (you will need a Google account).
• Create a folder for your notebooks (this step isn’t totally necessary if you want to just start working in Colab). You can do that by going to your Google Drive and clicking New and then creating a new folder. Then, if you want, while you’re already in your Google Drive you can create a new Colab notebook. Just click New and drop the menu down to More and then select Colaboratory. Otherwise, you can always go directly to Google Colab.
• Set up a free GPU (when using deep learning). Go to the runtime dropdown menu, selecting change runtime type and selecting GPU in the hardware accelerator drop-down menu.
• Get coding!

Colab FAQ