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Machine learning is software applications being able to predict data without the software being told explicitly to do so. Now there are different types of machine learning and we will go into them to get a better view of the ML world.
Unsupervised machine learning
This type of ML trains on non–labelled data and scans these data looking for any meaningful connections to make the right kind of predictions. Used in recommender systems, Netflix and YouTube algorithms are a great example of unsupervised learning systems. Also face detection is also a good example.
here data has labels as it is told exactly what to do so that when the ai goes out to look for data it needs to, it knows exactly what it Is looking for. Used to predict stock prices and housing prices in the market
This is where the user will make trial and errors to know what to look for, it is penalized and rewarded which may help the AI get closer to its goal. This is used in gaming where machine will act as a player and try win a game (think AlphaGo(link)), robotics – where robots will start interacting with the world.
Machine learning is at the forefront of tech right now and seems to be the future of tech, machine learning can not only be used in software like Netflix and Instagram, but also in robotics, manufacturing, and more industries to come.
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