AI Fundamentals

What is ‘feature engineering’ in traditional machine learning?

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What is the ‘transformer architecture’ and why was it revolutionary for AI?

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What is ‘self-attention’ in transformer models?

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What is ‘cross-validation’ in machine learning model evaluation?

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What is ‘underfitting’ in machine learning?

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What is ‘backpropagation’ in neural network training?

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What is an ‘activation function’ in a neural network?

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What is a ‘loss function’ in machine learning?

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What is the difference between ‘parameters’ and ‘hyperparameters’ in machine learning?

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What is ‘gradient descent’ in neural network training?

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What is ‘inference’ in machine learning deployment?

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What is the ‘Turing Test’?

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What is ‘transfer learning’ in AI?

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What is ‘bias’ in the context of AI models?

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What is a ‘GPU’ and why is it important for AI?

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What is ‘regression’ in machine learning?

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What is ‘classification’ in machine learning?

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What is a ‘dataset’ in machine learning?

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