Neural Networks are a subset of machine learning that are inspired by the way our brains work. These systems use a series of layers, or neurons, to predict a result based on previous inputs.
Neural networks are unique because they can generalize: they don't just know how to do one thing (like recognize objects), but instead can learn how to do many different things based on the data they're fed. That's why deep learning is so powerful—it's a way for machines to learn from their mistakes and get better at doing something over time.
There's still quite a lot we need to learn about neural networks before we can use them reliably in everyday life (like medicine or self-driving cars). But it looks like this technology is going to be big!
Neural networks are unique because they can generalize: they don't just know how to do one thing (like recognize objects), but instead can learn how to do many different things based on the data they're fed. That's why deep learning is so powerful—it's a way for machines to learn from their mistakes and get better at doing something over time.
There's still quite a lot we need to learn about neural networks before we can use them reliably in everyday life (like medicine or self-driving cars). But it looks like this technology is going to be big!
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