Deep Learning

A special type of machine learning that thinks in layers to gradually understand more complex ideas. This is based on how the human brain processes information.

• Best for working with large or high volume datasets
• Has higher overhead and is slower than ML

How It Works

It uses artificial neural networks which are basically computer models inspired by how our brain's neurons connect and network together.

The deep in deep learning refers to the many layers of these networks, each layer transforms input in to something more useful for the next layer.

Example:

• Input data
• Layer 1 - detect shapes in an image
• Layer 2 - detects parts of an object
• Layer 3 - Identifies whole object
• Output layer - makes predictions

Why Its Important

• Recognizing patterns in large datasets
• Ability to adapt and improve automatically with additional information
• Handles complex tasks that humans do naturally