Heat Maps
Heat maps are a graphical representation of data where values are depicted using colors. The colors in the map represent different levels of intensity, with darker colors indicating higher values and lighter colors indicating lower values. Heat maps are commonly used in data science to visualize large datasets and identify patterns or trends. They are particularly useful for identifying areas of high or low concentration, such as population density or customer activity. Heat maps can be created using various software tools and programming languages, such as Python, R, and Tableau. They are often used in fields such as marketing, finance, and healthcare to analyze and interpret complex data sets.
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- Eigenvectors: In linear algebra, eigenvectors are the non-zero vectors that only change by a scalar factor when a linear transformation is applied to them. In data science, eigenvectors are used in principal component analysis (PCA) to reduce the dimensi ... Read More >>
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