A set of instructions or rules that a computer follows to solve a problem or accomplish a task. Think of it like a recipe.
A program that has been trained on a set of data to perform a specific task. It's the 'finished' product of machine learning.
The process of teaching a machine learning model by feeding it data and allowing it to adjust its internal parameters (weights) to minimize errors.
The phase where a trained model is put to work, making predictions or decisions based on new, unseen data.
A broad field of computer science dedicated to creating systems capable of performing tasks that typically require human intelligence.
A subset of AI where computers learn from data without being explicitly programmed for specific rules.
A specialized type of machine learning that uses neural networks with many layers (hence 'deep') to model complex patterns in data.
A method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain.
Parameters within a neural network that transform input data within the network's hidden layers. They determine the importance of the input to the output.
A type of machine learning where the model is trained on a labeled dataset (data with known answers).
A type of machine learning where the model tries to find patterns and relationships in unlabeled data.
The automated recognition of patterns and regularities in data.
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