.. _Learn:

===================
Learn
===================

News and articles
~~~~~~~~~~~~~~~~~

- `What are Gaussian Processes? <https://www.digilab.co.uk/posts/what-are-gaussian-processes>`_
- `The Kernel Cookbook <https://www.digilab.co.uk/posts/the-kernel-cookbook>`_
- `autoML in twinLab <https://www.digilab.co.uk/posts/automl-in-twinlab>`_
- `Predict in twinLab <https://www.digilab.co.uk/posts/predict-in-twinlab>`_
- `Initial Design Space <https://www.digilab.co.uk/posts/twinlab-feature-release-initial-design-space>`_
- `Dimensionality Reduction for Functional Data <https://www.digilab.co.uk/posts/twinlab-feature-release-dimensionality-reduction-for-functional-data>`_

ML short courses
~~~~~~~~~~~~~~~~

- `Getting Started in Machine Learning <https://www.digilab.co.uk/course/getting-started-in-machine-learning>`_
- `Using General Linear Models for Machine Learning <https://www.digilab.co.uk/course/general-linear-models-for-machine-learning>`_
- `The Kernel Trick <https://www.digilab.co.uk/course/the-kernel-trick-flexible-machine-learning>`_
- `Tree-based algorithms: Random Forests and Gradient Boosted Trees <https://www.digilab.co.uk/course/random-forests-and-gradient-boosted-trees>`_
- `An Introduction to Bayesian Uncertainty Quantification <https://www.digilab.co.uk/course/uncertainty-quantification-for-machine-learning>`_
- `AI Ethics <https://www.digilab.co.uk/course/ai-ethics-fairness-and-balance-in-modern-ml>`_
- `Production-Ready Neural Network-Powered Web App <https://www.digilab.co.uk/course/building-a-neural-network-powered-web-app>`_
- `Data Cleaning in Excel and Python <https://www.digilab.co.uk/course/strategies-and-techniques-for-data-cleaning-in-excel-and-python>`_
- `Deep Learning 101: Getting Started with Neural Networks <https://www.digilab.co.uk/course/deep-learning-and-neural-networks>`_

.. seealso::

   Start evaluating your own problems with help from our :ref:`Python documentation <api>`.

   Let us know if you get stuck - we're always `happy to help <https://www.digilab.co.uk/contact>`_!