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What is Data Structure?

Data structure refers to an organized way of storing and managing data efficiently. Common types include arrays, linked lists, stacks, queues, trees, and graphs. It forms the foundation of algorithms and software development, optimizing search, sorting, and data manipulation tasks. Data structures are critical in database design, AI models, and real-time computing systems.

Source data
Source data refers to the original, unaltered information collected from primary sources before any processing or analysis. It serves as the foundation for data-driven decision-making in research, AI training, and analytics.
Data Augmentation
Data augmentation is a technique used in machine learning to artificially expand a dataset by applying transformations such as rotation, scaling, flipping, or noise injection. It helps improve model performance by increasing data diversity, particularly in image, speech, and text recognition tasks. Data augmentation is essential in deep learning to reduce overfitting and enhance model generalization.
Statistical data types
Statistical data types refer to the classification of data into categories such as nominal, ordinal, interval, and ratio data. Understanding these types helps in selecting appropriate analysis methods and visualization techniques.

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