Installation#

Python Version#

We recommend using the latest stable version of Python. Brisk supports Python 3.10 and later.

Dependencies#

Several packages will be installed automatically when you install Brisk. We recommend using a virtual environment, such as venv or conda, to manage dependencies.

  • scikit-learn: provides many of the machine learning tools used in Brisk.

  • pandas: provides dataframes for working with structured data.

  • numpy: provides support for arrays, matrices, and a wide range of mathematical functions.

  • matplotlib: provides plotting functionality for creating visualizations.

  • seaborn: provides a high-level interface for visualizations.

  • plotnine: provides a grammar of graphics for creating plots.

  • jinja2: provides templating functionality for rendering HTML templates.

  • tqdm: provides progress bars for visualizing the progress of loops and long-running tasks.

  • joblib: provides tools for serializing and de-serializing objects.

  • openpyxl: provides tools for working with Excel files.

Install Brisk#

Activate your virtual environment and then install Brisk using pip:

pip install brisk-ml

Verify the Installation#

You can verify the installation by running the following command:

pip show brisk-ml

This will print information about the installed package, including the version number. The version number should be 1.0.1.

With Brisk installed you are ready to create your first project!