Have you ever wondered how the program filters certain mails as spam after marking an email as one without you explicitly giving it as an order? Or how do searching engines give you plentiful suggestions when you haven’t even finished writing? Well, this is what machine learning is about and today we’re going to discover more about it in this article !
What is machine learning?
Scientists haven’t agreed on a definition yet, but it could be defined as giving computers the ability to learn without being explicitly ``taught`` since the program will do so from experience respecting some tasks and performance measures (the process of collecting, analyzing, and/or reporting information regarding the performance of an individual).
It’s considered a branch of AI (artificial intelligence) and could also be defined as a method of data analysis that identifies a pattern and makes decisions with minimal human intervention.
How does it work?
The three important units of machine learning system are:
*The model, a system that makes predictions
*The parameters, factors considered by the model to make the prediction
*The learners, the adjustments in the parameters, and the model to align the predictions with actual results
A typical machine learning process can be summed to : TRAINING—>VALIDATION—>TESTING.
Some examples of machine learning:
Machine learning can be found in image recognition systems. A well-known example is assigning a name to photographed faces in the phone gallery (sometimes it could even read the emotion of the person!).
It’s also used in the very well-known searching tool Google. This platform uses machine learning to personalize the experience of every user.
Why should you learn about machine learning:
With every industry looking to include AI in its domain, studying machine learning is a great way to open new opportunities and broaden your horizon. It’s the shining star of the moment and the key to the future.
Source: -coursera : https://coursera.org/learn/machine-learning
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