Neural Network

What is a Neural Network?

A neural network is a type of machine learning model loosely inspired by the human brain. It consists of layers of interconnected nodes (artificial neurons) that process data by applying weights, biases, and activation functions to transform inputs into outputs.

Neural networks are the foundation of deep learning and power most modern AI systems, including image recognition and content moderation.

Neural Network Architecture

• Input layer: Receives raw data (image pixels)
• Hidden layers: Process and transform data through learned features
• Output layer: Produces predictions (content categories)
• Weights: Adjustable parameters learned during training
• Activation functions: Add non-linearity for complex pattern learning

Types for Image Analysis

• CNN (Convolutional Neural Network): Specialized for image analysis, using convolutional layers to detect visual patterns
• ResNet: Deep CNNs with skip connections for very deep networks
• Vision Transformers: Newer architecture using attention mechanisms

Neural Networks in Moderation

Content moderation systems use neural networks trained on millions of labeled images to recognize patterns associated with different content types. The networks learn hierarchical features - from edges and textures to objects and scenes - enabling accurate classification of new images.