Deep learning is a subfield of machine learning that focuses on the development and training of neural networks to perform tasks that traditionally require human intelligence. It has gained significant attention and popularity due to its ability to automatically learn hierarchical representations of data, allowing it to capture complex patterns and features. Here’s an overview of deep learning and its key differences from traditional machine learning:
I. What is Deep Learning?
1. Definition:
Deep learning involves training artificial neural networks with multiple layers (deep neural networks) to recognize patterns, make decisions, and perform tasks without explicit programming. The term “deep” refers to the depth of the neural network, which comprises multiple layers (also called hidden layers) between the input and output layers.
2. Key Components:
- Neural Networks: The fundamental building blocks of deep learning, modeled after the structure of the human brain, consisting of interconnected nodes or neurons.
- Layers: Deep neural networks consist of an input layer, one or more hidden layers, and an output layer. Each layer contains…
