We will use Jupyter Notebooks for all exercises. There are several ways to set up a Jupyter environment for running the exercises:
The default option. CSC’s Notebooks (https://notebooks.csc.fi) provides easy-to-use environments for working with data and programming. You can access everything via your web browser and CSC cloud environment computes on the background.
- Point your browser to https://notebooks.csc.fi
- Login using Haka or a CSC account (or using Alternate login and a separate username and password)
- Find Course Practical Machine Learning 2019 and click “Launch new”
- Wait until the “Open in browser” link appears, then click on it
- The JupyterLab notebook dashboard should appear
- If you are not familiar with Jupyter, take a moment to get to know the interface
- open a new notebook using the Launcher (click on Notebook: Python 3)
- write some Python code to a Jupyter cell
- execute the cell with shift-enter
- Exercise 1: Navigate to
python-introduction/notebooks/examples
and go through the notebooks 1 - Introduction.ipynb and 7 - NumPy.ipynb. - Other exercises: Navigate to
intro-to-ml
where all the exercise notebooks are located
If you have a laptop that has Jupyter, Scikit-learn, and all the other necessary Python packages installed, it is possible to use it. Clone the Git repositories used on this course
git clone https://github.com/csc-training/python-introduction
git clone https://github.com/csc-training/intro-to-ml
and launch Jupyter.