Supervised Learning - Classification

Supervised Learning

In supervised learning, the algorithm is given labeled examples in order to come up with an appropriate model that defines the data and can also correctly label future examples correctly (or adequately). Supervised learning can be grouped into the following depending on the actual label type:

  1. Binary Classification (think yes/no)
  2. Multi-class classification (any answer from a finite set)
  3. Rgression (any answer from an infinite set)

In the machine library I am trying to put together, each of the three groups mentioned above can be separated into distinct .NET data types as follows:

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What is Machine Learning?

Introduction

I had the priviledge of presenting at CodeStock. It was absolutely great. I was surprised and humbled at the reception of my session regarding Machine Learning. As such, I wanted to do a series of posts regarding what it is I wish to accomplish.

Machine Learning is Hard

Because the stuff is so intriguing, I have spent the last number of years trying to figure the stuff out! I would certainly not classify myself as an expert (by any means), but I think I have a general idea of the field.

Machine learning can be seperated into roughly 3 classifications:

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