query: What is machine learning?

documents: Machine learning is a subset of artificial intelligence that enables systems to learn from data.

documents: 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.

documents: 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.

documents: 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.

documents: 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.

documents: 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.

documents: 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.

documents: 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.

documents: 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.

documents: 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.

documents: It iteratively adjusts model parameters in the direction of steepest descent of the loss function.