Today, I will be giving you a brief introduction and history of Deep Learning. Deep Learning is as close as we have gotten towards mirroring the functionality of brains in computationally efficient systems.
The past decade has seen incredible advancements in Deep Learning. It has opened so many new paradigms for Artificial Intelligence and taken our capability of making intelligent machines to a whole new level. Today, I will be giving you a brief introduction and history of Deep Learning.
Deep Learning is as close as we have gotten towards mirroring the functionality of brains in computationally efficient systems. This picture from an MIT Deep Learning lecture which outlines the current advancement stage perfectly
Deep Learning is largely based on the idea of neural networks which is based on the workings of our brain. For now, you can understand neural networks as something that has a strong biological inspiration. So before diving into the concept let’s discuss why neural networks and deep learning has been so successful recently even though it was released ages back:
Now we have a good idea of why Deep Learning is exploding let’s get into the functioning of a neural network. Like I said they are inspired by the human brain and the basic building block of a brain is a perceptron which looks a lot like this:
This perceptron has a set of dendrites a cell body and a set of axon terminals. If you think about it, it looks like the dendrites receive information the cell understands and processes the information and the axon terminals pass its processed information forward. Just like a perceptron works, computer scientists tried to develop a ‘neuron’ system that can mimic brain functioning and process data to find various patterns. And thus a system like this was born:
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