Isomap

Isomap is a nonlinear dimensionality reduction technique used to preserve the intrinsic geometry of high-dimensional data by mapping it to a lower-dimensional space. As big data continues to grow, Isomap is particularly relevant to the tech community for its ability to simplify complex datasets, making it easier to visualize and analyze them, which is crucial in applications such as data mining, machine learning, and pattern recognition.