Introduction to Machine Learning

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Machine learning is a system of algorithms aimed at detecting patterns in big data and then learning from those patterns without being explicitly programmed by a human operator. These algorithms take a probabilistic, rather than a deterministic, approach to accomplishing goals. Let’s take a quick look at what that means by way of example:

Deterministic Approach

A human programs software in no uncertain terms to remind him to bring his umbrella to work if the chance of precipitation in his area is greater than 40%:

//Get the weather forecast
var chanceOfRain = myWeatherForecast().precipitationChance;

//Send the message
if(chanceOfRain > 40%){
    sendEmail("Bring your umbrella to work!");
}

This approach is deterministic because the outcome is predetermined by the author of the code in no uncertain terms.

Probabilistic (Machine Learning) Approach

An algorithm crawls big datasets such as tweets about the weather, weather news, forecasts, umbrella sales, and supervised feedback (we’ll get to that later) such as, “did you bring an umbrella to work today?”:

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