NumPy is a fundamental Python library for numerical computing that provides efficient multi-dimensional arrays and mathematical operations. The tutorial covers installation, array creation (1D, 2D, 3D), data types, indexing and slicing, element-wise and scalar operations, reshaping, statistical functions, and linear algebra operations. Practical examples demonstrate image processing (brightness/contrast adjustment) and data analysis (student test scores). NumPy arrays are significantly faster than Python lists for numerical operations due to underlying C/C++ implementation, making them essential for data science, machine learning, and scientific computing workflows.
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