Machine Learning

What is Machine Learning?

Machine learning is a branch of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed. In content moderation, ML models are trained on millions of labeled images to recognize patterns associated with different content types.

These models can then classify new, unseen images with high accuracy, enabling platforms to moderate content at scales impossible for human teams alone.

Types of Machine Learning

• Supervised learning: Models trained on labeled data (most common in moderation)
• Unsupervised learning: Finding patterns without labeled examples
• Deep learning: Neural networks with many layers for complex patterns
• Transfer learning: Adapting pre-trained models to new tasks

How ML Models Learn

Content moderation ML models are trained using large datasets of images labeled by human annotators. The model learns to associate visual features with content categories. During training, the model adjusts its parameters to minimize prediction errors.

ML Model Performance

ML model quality is measured through metrics like precision, recall, and F1 score. The best models balance catching harmful content (high recall) with avoiding false positives (high precision). Continuous training on new data helps models adapt to evolving threats.