by Benjamin Villalonga Correa

Introduction to Supervised Machine Learning

With Supervised Machine Learning techniques we can train a model to be able to recognize and classify inputs such as handritten digits, human faces, objects in a picture or sports teams with high chances of winning a game. One of the most used strategies for doing so is the use of artificial neural networks.

Presentation Summary

In this presentation, I talk about:

  • the basic problem setup for supervised machine learning.
  • the classical example of MNIST.
  • a motivation for using neural networks.
  • some easy to code results.
  • some intuition on what a neural network is actually doing.


  • Excelent tutorials for examples are given by the TensorFlow website team.
  • A great (online and free) book on neural networks and deep learning is Nielsen’s textbook.


All Machine Learning.

artificial intelligence machine learning supervised machine learning neural networks