Vectorization is the process of converting operations into a format that can be executed on multiple data points simultaneously, rather than one at a time. This technique is commonly used in programming and data analysis to improve performance and efficiency. By using vectors, which are arrays of numbers, computations can be performed in parallel, significantly speeding up tasks like mathematical calculations and data processing. In the context of machine learning, vectorization allows algorithms to handle large datasets more effectively. For example, libraries like NumPy in Python utilize vectorization to perform operations on entire arrays, reducing the need for explicit loops and enhancing computational speed. This is particularly beneficial in tasks such as linear algebra and statistical analysis.