Neural Network is a machine learning model inspired by the structure and functioning of the human brain. It consists of interconnected layers of nodes (neurons) that process data, recognize patterns, and make predictions or decisions.
In artificial intelligence and deep learning, neural networks are used to solve complex tasks such as image recognition, speech processing, language understanding, and recommendation systems. They learn by adjusting connections (weights) between neurons during training.
For example:
- A facial recognition system identifies people from images using neural networks.
- Voice assistants process and understand spoken language through deep learning models.
- Recommendation systems suggest movies or products based on user behavior.
- Self-driving cars analyze road signs and obstacles using neural networks.
Common technologies and concepts related to neural networks include:
- Deep Learning
- Artificial Intelligence (AI)
- Input, Hidden, and Output Layers
- Training Data
- Weights & Biases
- Backpropagation
- TensorFlow / PyTorch
- Computer Vision
- Natural Language Processing (NLP)
