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This PDF explores the foundations of AI models and training data, breaking down how intelligent systems are powered by structured, unstructured, and semi-structured data. It explains methods of data collection, the AI data lifecycle, and key training processes such as pattern recognition, parameter tuning, and transfer learning. The document also highlights performance metrics like accuracy, precision, recall, and F1 score, while addressing common challenges such as data scarcity, bias, privacy, and high resource demands. Innovative solutions, including few-shot learning, data augmentation, sy
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