AI: Vocabulary

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second language

5º - Educación secundaria (7+5)

Âge recommandé: 17 ans

2 fois fait

Créé par

Rocio Carmona

Argentina

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31 Mai 2024

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Relier Pairs AI: VocabularyVersion en ligne Match the words with its definition. par Rocio Carmona 1 Turing Machine 2 Machine Learning 3 Backpropagation 4 Lisp 5 Bias 6 Reinforcement Learning 7 Overfitting 8 Recurrent Neural Network (RNN) 9 Neural Network 10 Artificial Intelligence (AI) The simulation of human intelligence in machines that are programmed to think and learn like humans. A training algorithm for neural networks that adjusts weights by propagating the error gradient backward through the network to minimize the error. A systematic error in AI algorithms that can lead to unfair outcomes, often due to biased training data. A modeling error in machine learning where the model learns the training data too well, resulting in poor performance on new, unseen data. A subset of AI that involves training algorithms to learn from data and improve their performance over time without being explicitly programmed. A computational model inspired by the human brain, consisting of interconnected nodes (neurons) that process information in layers. A programming language developed by John McCarthy, specifically designed for AI research, known for its powerful symbolic processing capabilities. A type of machine learning where an agent learns to make decisions by receiving rewards or penalties based on its actions. A hypothetical computing device that formalizes the concept of computation and can simulate the logic of any computer algorithm. A type of neural network designed for processing sequences of data by having loops in the network architecture to maintain a memory of previous inputs

Relier Pairs

AI: VocabularyVersion en ligne

Match the words with its definition.

par Rocio Carmona

Turing Machine

Machine Learning

Backpropagation

Lisp

Bias

Reinforcement Learning

Overfitting

Recurrent Neural Network (RNN)

Neural Network

Artificial Intelligence (AI)

The simulation of human intelligence in machines that are programmed to think and learn like humans.

A training algorithm for neural networks that adjusts weights by propagating the error gradient backward through the network to minimize the error.

A systematic error in AI algorithms that can lead to unfair outcomes, often due to biased training data.

A modeling error in machine learning where the model learns the training data too well, resulting in poor performance on new, unseen data.

A subset of AI that involves training algorithms to learn from data and improve their performance over time without being explicitly programmed.

A computational model inspired by the human brain, consisting of interconnected nodes (neurons) that process information in layers.

A programming language developed by John McCarthy, specifically designed for AI research, known for its powerful symbolic processing capabilities.

A type of machine learning where an agent learns to make decisions by receiving rewards or penalties based on its actions.

A hypothetical computing device that formalizes the concept of computation and can simulate the logic of any computer algorithm.

A type of neural network designed for processing sequences of data by having loops in the network architecture to maintain a memory of previous inputs