AI & ML Foundations
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Terms in this set
- Artificial Intelligence The broad field of building systems that perform tasks normally requiring human intelligence.
- Machine Learning Systems that learn patterns from data to make predictions without being explicitly programmed.
- Deep Learning Machine learning that uses multi-layer neural networks to learn complex patterns.
- Neural Network Interconnected layers of nodes ('neurons') loosely modeled on the brain that learn weighted patterns.
- Supervised Learning Training a model on labeled examples so it can predict labels for new data.
- Unsupervised Learning Finding structure in unlabeled data, such as grouping similar items together.
- Reinforcement Learning An agent learns by taking actions and receiving rewards or penalties from its environment.
- Inference Using a trained model to make predictions or generate output on new input.
- Training Data The dataset a model learns from during training.
- Bias Systematic error in a model, often from unrepresentative training data, that skews predictions.