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  2. erwin Data Modeler - Wikipedia

    en.wikipedia.org/wiki/Erwin_Data_Modeler

    erwin Data Modeler (stylized as erwin but formerly as ERwin) is computer software for data modeling.Originally developed by Logic Works, erwin has since been acquired by a series of companies, before being spun-off by the private equity firm Parallax Capital Partners, which acquired and incorporated it as a separate entity, erwin, Inc., managed by CEO Adam Famularo.

  3. Comparison of data modeling tools - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data...

    Update database and/or update model No Oracle SQL Developer Data Modeler Logical, physical Barker, IE (Crow’s foot), and Bachman Yes Yes Update database and/or update model Yes PowerDesigner: Conceptual, logical, physical IDEF1X, IE (Crow’s foot), and more Yes Yes Update database and/or update model Yes Software Ideas Modeler

  4. Educational data mining - Wikipedia

    en.wikipedia.org/wiki/Educational_data_mining

    For example, the learning curve, classic to educational studies, is a pattern that clearly reflects the relationship between learning and experience over time. Data is also distilled for the purposes of classifying features of data, which for educational data mining, is used to support the development of the prediction model.

  5. Data-driven model - Wikipedia

    en.wikipedia.org/wiki/Data-driven_model

    Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]

  6. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce ...

  7. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The use of different model parameters and different corpus sizes can greatly affect the quality of a word2vec model. Accuracy can be improved in a number of ways, including the choice of model architecture (CBOW or Skip-Gram), increasing the training data set, increasing the number of vector dimensions, and increasing the window size of words ...

  8. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Software Creator Initial release Software license [a] Open source Platform Written in Interface OpenMP support OpenCL support CUDA support ROCm support [1] Automatic differentiation [2] Has pretrained models Recurrent nets Convolutional nets RBM/DBNs Parallel execution (multi node) Actively developed BigDL: Jason Dai (Intel) 2016 Apache 2.0 ...

  9. Database design - Wikipedia

    en.wikipedia.org/wiki/Database_design

    Database design is the organization of data according to a database model. The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model. [1] A database management system manages the data accordingly.

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