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Short guide to deploy Machine Learning

"Calling ML intricately simple 🙂 "

Suppose you have a problem that you like to tackle with machine learning and use the resulting system in a real-life project.  I like to share my simple pathway for such purpose, in order to provide a basic guide to beginners and keep these things as a reminder to myself. These rules are tricky since even-thought they are simple, it is not that trivial to remember all and suppress your instinct which likes to see a running model as soon as possible.

When we confronted any problem, initially we have numerous learning algorithms, many bytes or gigabytes of data and already established knowledge to apply some of these models to particular problems.  With all these in mind, we follow a three stages procedure;

  1. Define a goal based on a metric
  2. Build the system
  3. Refine the system with more data

Let's pear down these steps into more details ; Continue reading Short guide to deploy Machine Learning