Deep learning neurons are modelled like neurons in the human brain. Neurons have an intriguing structure, as you can see. Inside the human brain, groups of neurons collaborate to conduct the functions we require on a daily basis. During his groundbreaking research in neural networks, Geoffrey Hinton wondered whether we might create computer algorithms that behaved similarly to neurons in the brain. We hoped to capture some of the brain's capabilities by imitating its shape.

To accomplish so, researchers looked at how neurons in the brain functioned. One key finding was that a neuron by itself is ineffective. To develop any significant functioning, you need networks of neurons.

Because neurons receive and transmit messages, this is the case. The dendrites of the neuron receive signals and transmit them through the axon. One neuron's dendrites are attached to another neuron's axon. These connections are called synapses, which is a concept that has been generalized to the field of deep learning.


This post is for paying subscribers only

Sign up now and upgrade your account to read the post and get access to the full library of posts for paying subscribers only.

Sign up now Already have an account? Sign in