These posts introduce the background theory necessary to implement different aspects of machine learning. The explanations are surface level but there a links to further reading were relevant. Each post contains a link one or more jupyter notebooks that load in Google Colab and demonstrate the ideas presented.

Topics

  1. Introduction to classification and regression with neural networks

    2. This post covers some of the basic concepts that are necessary to understand neural networks and implement them for basic supervised classification and regression task.

  2. Convolutional neural networks for classification

    3. An intro