Deep Learning: Biological Neural Network vs Artificial Neural Network.

Author(s): Chandra Prakash Bathula

Originally published on Towards AI.

The Biological Blueprint of Deep Learning

In this series of blogs, we’re diving deep into deep neural networks, their variations, and transformers. So far, we’ve explored the history of neural networks. Now, let’s see how a single biological neuron inspired artificial neural networks and how this inspiration evolved over time.

This article explores the foundational principles of deep learning, drawing from the intricacies of biological neural networks. It compares the functioning of biological neurons with artificial ones, emphasizing aspects like dendrite importance, activation functions, and weight variation in inputs. As the article unfolds, it discusses how the complexity of neural connections increases with experiences, highlighting differences in information processing, and presents mathematical representations of neural networks to illustrate how they emulate biological counterparts.

Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI