Deep learning is transforming technology as we know it, enabling machines to analyze and interpret the world around us. This guide provides a straightforward overview of deep learning, focusing on its core principle: neural networks. By simplifying complex concepts, we aim to make this innovative field accessible to everyone interested in learning how machines can perform tasks that typically require human intelligence.
WHAT IS IT?
Deep Learning is a type of Machine Learning that uses neural networks with multiple layers (hence “deep”) to analyze various forms of data, such as images, sound, and text. It mimics the way human brains operate, learning from large amounts of data.
Components and Process:
1. Basic Structure of Neural Networks:
- Input Layer: This is where the network receives its raw data, like the pixels of an image.
- Neurons: Think of these as the brain cells of the computer. Each neuron performs simple calculations to transform the input data.
- Hidden Layers: These are layers of neurons placed between the input and output layers. They help in recognizing complex patterns in the data.
- Output Layer: It…
