Machine learning (ML) is simply a collective term for a number of very different techniques (neural nets, clustering etc.). To use ML effectively you have to know what these techniques are and what they do. You don’t need to understand the detail, any more than you need to know how a battery works to drive a Tesla. What you do need is a good handle on the main types of ML, their strengths and weaknesses.
This presentation, Machine learning: A Practitioner’s Guide provides an understanding of the main types of Machine Learning in non-technical terms, along with their strengths and weaknesses, creating the foundations necessary to use Machine Learning effectively.
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