How to Define Your Machine Learning Problem

Last Updated on June 7, 2016

The first step in any project is defining your problem. You can use the most powerful and shiniest algorithms available, but the results will be meaningless if you are solving the wrong problem.

In this post you will learn the process for thinking deeply about your problem before you get started. This is unarguably the most important aspect of applying machine learning.

What is the problem?

What is the problem?
Photo attributed to Eleaf, some rights reserved

Problem Definition Framework

I use a simple framework when defining a new problem to address with machine learning. The framework helps me to quickly understand the elements and motivation for the problem and whether machine learning is suitable or not.

The framework involves answering three questions to varying degrees of thoroughness:

  • Step 1: What is the problem?
  • Step 2: Why does the problem need to be solved?
  • Step 3: How would I solve the problem?

Step 1: What is the Problem

The first step is defining the problem. I use a number of
To finish reading, please visit source site