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Here’s a basic definition of machine learning:
“Algorithms that parse data, learn from that data, and then apply what they’ve learned to make informed decisions”.
Machine learning fuels all sorts of automated tasks and spans across multiple industries, from data security firms hunting down malware to finance professionals looking out for favourable trades. They’re designed to work like virtual personal assistants, and they work quite well.
Machine learning is a lot of complex math and coding that, at the end of the day, serves a mechanical function. the same way as a flashlight, a car, or a television does. When something is capable of “machine learning”. it means it’s performing a function with the data given to it and gets progressively better at that function. 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”.
Now, the way machines can learn new tricks gets really interesting (and exciting) when we start talking about deep learning.
A deep learning model is designed to continually analyze data with a logic structure similar to how a human would draw conclusions. To achieve this, deep learning uses a layered structure of algorithms called an artificial neural network (ANN). The design of an ANN is inspired by the biological neural network of the human brain. This makes for machine intelligence that’s far more capable than that of standard machine learning models.
A great example of deep learning is Google’s AlphaGo. Google created a computer program that learned to play the abstract board game called Go. a game is known for requiring sharp intellect and intuition. By playing against professional Go players, AlphaGo’s deep learning model learned how to play at a level not seen before in artificial intelligence, and all without being told when it should be made a specific move (as it would with a standard machine learning model). It caused quite a stir when AlphaGo defeated multiple world-renowned “masters” of the game; not only could a machine grasp the complex and abstract aspects of the game, it was becoming one of the greatest players of it as well.
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