Real World Data Science Project : Plant Disease Prediction

Free Courses : Real World Data Science Project : Plant Disease Prediction

Algorithms that parse data, learn from that data, and then apply what theyve learned to make informed decisions

An easy example of a machine learning algorithm is an on-demand music streaming service. For the service to make a decision about which new songs or artists to recommend to a listener, machine learning algorithms associate the listeners preferences with other listeners who have a similar musical taste. This technique, which is often simply touted as AI, is used in many services that offer automated recommendations.

Machine learning fuels all sorts of automated tasks that span across multiple industries, from data security firms that hunt down malware to finance professionals who want alerts for favorable trades. The AI algorithms are programmed to constantly be learning in a way that simulates as a virtual personal assistantsomething that they do quite well.

Machine learning involves a lot of complex math and coding that, at the end of the day, serves a mechanical function the same way a flashlight, a car, or a computer screen does. When we say something is capable of machine learning, it means its something that performs a function with the data given to it and gets progressively better over time. It's like if you had a flashlight that turned on whenever you said it's dark, so it would recognize different phrases containing the word "dark."

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