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  2. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    To use column-major order in a row-major environment, or vice versa, for whatever reason, one workaround is to assign non-conventional roles to the indexes (using the first index for the column and the second index for the row), and another is to bypass language syntax by explicitly computing positions in a one-dimensional array.

  3. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Goldberg and Levy point out that the word2vec objective function causes words that occur in similar contexts to have similar embeddings (as measured by cosine similarity) and note that this is in line with J. R. Firth's distributional hypothesis. However, they note that this explanation is "very hand-wavy" and argue that a more formal ...

  4. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster.

  5. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python has array index and array slicing expressions in lists, denoted as a[key], a [start: stop] or a [start: stop: step]. Indexes are zero-based, and negative indexes are relative to the end. Slices take elements from the start index up to, but not including, the stop index.

  6. Pivot table - Wikipedia

    en.wikipedia.org/wiki/Pivot_table

    Column labels are used to apply a filter to one or more columns that have to be shown in the pivot table. For instance if the "Salesperson" field is dragged to this area, then the table constructed will have values from the column "Sales Person", i.e., one will have a number of columns equal to the number of "Salesperson". There will also be ...

  7. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Sparse dictionary learning is a feature learning method where a training example is represented as a linear combination of basis functions and assumed to be a sparse matrix. The method is strongly NP-hard and difficult to solve approximately. [70] A popular heuristic method for sparse dictionary learning is the k-SVD algorithm. Sparse ...

  8. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    This is an attempt to model or fit an equation line or curve to the data, such that Y is a function of X. [74] [75] Necessary condition analysis (NCA) may be used when the analyst is trying to determine the extent to which independent variable X allows variable Y (e.g., "To what extent is a certain unemployment rate (X) necessary for a certain ...

  9. Data dictionary - Wikipedia

    en.wikipedia.org/wiki/Data_dictionary

    The terms data dictionary and data repository indicate a more general software utility than a catalogue. A catalogue is closely coupled with the DBMS software. It provides the information stored in it to the user and the DBA, but it is mainly accessed by the various software modules of the DBMS itself, such as DDL and DML compilers, the query optimiser, the transaction processor, report ...