Six Levels of Auto ML. TL;DR

 By Medium - 2020-02-24

Description

In this blog post we propose a taxonomy of 6 levels of Auto ML, similar to the taxonomy used for self-driving cars. Here are the 6 levels: ●Level 3: Automatic (technical) feature engineering and…

Summary

  • Ability to come up with super-human strategies for solving hard ML problems without any input or guidance.
  • AutoML Classification Challenges One of the main difficulties when building a classification following the example of self-driving vehicles is that for vehicles we have a pretty good understanding and template for what automation would entail — the everyday examples of human car drivers.
  • Numerical data can be used by most ML algorithms in its raw form.
  • Location is a very strong signal for many real world problems, but oftentimes the datasets that we are given only contain the grossest location-based information, such as Zip Code.

 

Topics

  1. Machine_Learning (0.35)
  2. Backend (0.32)
  3. NLP (0.26)

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