Clarifying the types of Machine Learning

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3 different types of machine learning

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Top 10 uses of ML and AI

Machine learning is a popular expression in the technology realm right now, and in light of current circumstances: It speaks to a noteworthy step forward in how computers can learn.

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via Top 10 Uses of Machine Learning and Artificial Intelligence Today

Gentle Introduction to the Bias-Variance Trade-Off in Machine Learning

The prediction error for any machine learning algorithm can be broken down into three parts:

  1. Bias Error
  2. Variance Error
  3. Irreducible Error

The irreducible error cannot be reduced regardless of what algorithm is used. It is the error introduced from the chosen framing of the problem and may be caused by factors like unknown variables that influence the mapping of the input variables to the output variable.

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Understanding the difference
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The optimal balance of course is where bias and variance are at their minimum

Find out more here:

The Bias-Variance Trade-Off in Machine Learning

Principles of Artificial Intelligence & Machine Learning

The key takeaways from this presentation are the following:

  • We, as future business leaders, must be able to decipher the signal from the noise with regards to AI / ML
  • AI will have profound practical and ethical implications for our society
  • Getting started is not as difficult as you might think
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Examples of applications of AI

The initial presentation can be found here:

Presentation

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The presentation

The article encompassing the presentation is here:

AI and ML