Algorithms I: Classification

In this video micro-lab we take a look at a machine learning algorithm called k-nearest neighbor (knn) which uses a distance formula to determine an input’s category or class. We start to define a main branch of Machine Learning that is called supervised learning in which the correct answers are paired with the training data. We also develop some conceptual frameworks for how seemingly unrelated data might lead to accurate predictions of abstracted problems. Objectives for this module are:

  • Describe inputs and signals as they relate to ML models
  • Observe how visualizing data can lead to creative problem solving
  • Explain how seemingly simple data can be leveraged to make abstracted predictions