An Introduction to Deep Learning

Photo by Shubham Dhage on Unsplash

Deep learning is a subset of machine learning that mimics the structure and functioning of the human brain. It acquires knowledge from unstructured data and employs intricate algorithms to train artificial neural networks.

In deep learning, the primary focus is on neural networks, a cornerstone of Artificial Intelligence. These networks are trained to identify and process diverse data types, including text, numbers, images, and speech. Unlike traditional machine learning, deep learning deals with considerably more complex, diverse, and unstructured data, such as images, audio, and text files.

Central to deep learning is the neural network, typically resembling the illustrated image below:

Image by simplilearn

As depicted earlier, the neural network comprises an Input Layer, an Output Layer, and multiple Hidden Layers sandwiched in between. In any neural network, a minimum of one hidden layer is present, and a network is considered “deep” when it contains more than one hidden layer.

Now, let’s delve deeper into an in-depth examination of these various layers.

Input Layer: acts as the initial point for processing large amounts of data within…