AI and Applied AI Concepts

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What is Supervised Learning?

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A type of machine learning that uses ground truth and labeled data, requiring prior knowledge to approximate the relationship between input and output.

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What are the two categories of Supervised Learning?

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Classification (predicting a label) and Regression (predicting a quantity).

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What is Unsupervised Learning?

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A type of machine learning that does not use historical labels and learns the inherent structure of the data.

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What are the two categories of Unsupervised Learning?

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Clustering (dividing the population) and Association (rule-based learning model).

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What is Reinforcement Learning?

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A type of learning where the model maximizes its performance in a given situation by finding the best possible behavior or path through rewards or punishments.

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What is AI Architecture?

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The design of an AI model, defining how data flows, how information is processed, and how results are produced.

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What is a Convolutional Neural Network (CNN)?

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A type of AI architecture that is best for image and video analysis, using filters to scan images and detect patterns.

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What is a Recurrent Neural Network (RNN)?

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An AI architecture that is ideal for sequential data like text or time series, processing data in order and remembering previous inputs.

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What are Transformers in AI?

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An architecture that revolutionized language models by analyzing all data at once and understanding relationships without sequential processing.

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Why is data important in AI?

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AI models learn from data, not instructions. Better data leads to more accurate and fair AI systems.