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In many programming languages, map is a higher-order function that applies a given function to each element of a collection, e.g. a list or set, returning the results in a collection of the same type.
A Data Matrix on a Mini PCI card, encoding the serial number 15C06E115AZC72983004. The most popular application for Data Matrix is marking small items, due to the code's ability to encode fifty characters in a symbol that is readable at 2 or 3 mm 2 (0.003 or 0.005 sq in) and the fact that the code can be read with only a 20% contrast ratio. [1]
The output is a hash code used to index a hash table holding the data or records, or pointers to them. A hash function may be considered to perform three functions: Convert variable-length keys into fixed-length (usually machine-word -length or less) values, by folding them by words or other units using a parity-preserving operator like ADD or XOR,
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.
Word2vec is a group of related models that are used to produce word embeddings.These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words.
The PDF at the previous timestep is assumed inductively to be the estimated state and covariance. This is justified because, as an optimal estimator, the Kalman filter makes best use of the measurements, therefore the PDF for x k {\displaystyle \mathbf {x} _{k}} given the measurements Z k {\displaystyle \mathbf {Z} _{k}} is the Kalman filter ...
Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.
Full width at half maximum. In a distribution, full width at half maximum (FWHM) is the difference between the two values of the independent variable at which the dependent variable is equal to half of its maximum value.