{"query": "What is machine learning?", "documents": ["Machine learning is a subset of artificial intelligence that enables systems to learn from data.", "ML algorithms can identify patterns and make predictions without explicit programming."]}
{"query": "How do neural networks work?", "documents": ["Neural networks are computing systems inspired by biological neural networks in animal brains.", "They consist of interconnected nodes that process information through weighted connections and activation functions."]}
{"query": "What is the difference between supervised and unsupervised learning?", "documents": ["Supervised learning uses labeled data to train models, while unsupervised learning finds patterns in unlabeled data.", "Common supervised tasks include classification and regression, while clustering is a typical unsupervised task."]}
{"query": "What is deep learning?", "documents": ["Deep learning is a subset of machine learning that uses neural networks with multiple layers.", "Deep learning has revolutionized fields like computer vision, natural language processing, and speech recognition."]}
{"query": "How does natural language processing work?", "documents": ["NLP enables computers to understand, interpret, and generate human language.", "Modern NLP systems use transformer models and attention mechanisms to process text data."]}
{"query": "What is a convolutional neural network?", "documents": ["CNNs are specialized neural networks designed for processing grid-like data such as images.", "They use convolutional layers to automatically learn spatial hierarchies of features."]}
{"query": "What is reinforcement learning?", "documents": ["Reinforcement learning is a type of ML where agents learn to make decisions by receiving rewards or penalties.", "It's commonly used in robotics, game playing, and autonomous systems."]}
{"query": "What is overfitting in machine learning?", "documents": ["Overfitting occurs when a model learns the training data too well, including noise and outliers.", "Techniques like regularization, cross-validation, and dropout help prevent overfitting."]}
{"query": "What is a transformer model?", "documents": ["Transformers are neural network architectures based on self-attention mechanisms.", "They have become the foundation for modern language models like GPT and BERT."]}
{"query": "How does gradient descent work?", "documents": ["Gradient descent is an optimization algorithm used to minimize loss functions in machine learning.", "It iteratively adjusts model parameters in the direction of steepest descent of the loss function."]}