Ask HN: Machine Learning overview for non-engineers

8 points·servo··3 comments

My boss is impressed with a small project for document classification that we have done as a side-project and want to have an idea of what kind of things can be done using machine learning and how this can be applied to the business.

Which references can I pass to him to explain what can be done using ML algorithms? I prefer short documents, I think he will not read an entire book about the subject.

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Putting on my @patio11 disguise: maybe you should write up a paragraph or two about the major 'flavors' of machine learning (classifier, regression, nearest-neighbor, NLP, etc) and an example of how they could be used in a business context. e.g. classifier for detecting spam, regression model to predict when customer is going to churn, nearest-neighbor for making a list of similar products in a catalogue.

Throw it up on Github pages, slap an email form on that and get a mailing list going. Seems genuinely useful and might generate good leads for a consulting company or to sell ML training.

Bearing in mind that the boss has access to expert colleagues whom can be asked for clarifications and explanations.

Option 1: The boss uses Google themselves, thereby allowing them to find resources at an appropriate technical level and then move along the gradient of technical detail as their knowledge deepens.

Option 2: "Alice in Wonderland"...because it's the best book on anything for the layman. Alan J. Perlis, Epigram 48 http://www.cs.yale.edu/homes/perlis-alan/quotes.html

Option 3: Arbitrary poor substitute for options 1 and 2.

Ah but we must not forget the Tao Book 7 http://www.mit.edu/~xela/tao.html

"You can demonstrate a program for a corporate executive, but you can't make him computer literate."

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