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DEEP LEARNING, NEURAL NETWORKS
6 Types of Neural Networks Every Data Scientist Must Know
The most common types of Neural Networks and their applications
Neural networks are robust deep learning models capable of synthesizing large amounts of data in seconds. There are many different types of neural networks, and they help us in a variety of everyday tasks from recommending movies or music to helping us buy groceries online.
Similar to the way airplanes were inspired by birds, neural networks (NNs) are inspired by biological neural networks. Though the principles are the same, the process and the structures can be very different. This is as true for birds and planes as it is for biological neural networks and deep learning neural networks.
To help put it into perspective, let’s look briefly at the biological neuron structure. Figure 1 shows the anatomy of a single neuron. The central part is called the cell body, where the nucleus resides. Various connections pass the stimulus to the cell body, called dendrites, and a few connections send the output to the other neurons called axons. The thickness of the dendrites and axons implies the power of the stimulus. Many neurons with various cell bodies are stacked up and form a biological neural network.
