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  2. Data entry clerk - Wikipedia

    en.wikipedia.org/wiki/Data_entry_clerk

    A data entry clerk. A data entry clerk, also known as data preparation and control operator, data registration and control operator, and data preparation and registration operator, is a member of staff employed to enter or update data into a computer system. [1][2] Data is often entered into a computer from paper documents [3] using a keyboard. [4]

  3. Data entry - Wikipedia

    en.wikipedia.org/wiki/Data_entry

    Data entry. Data entry is the process of digitizing data by entering it into a computer system for organization and management purposes. It is a person-based process [1] and is "one of the important basic" [2] tasks needed when no machine-readable version of the information is readily available for planned computer-based analysis or processing.

  4. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    The data, known as training data, consists of a set of training examples. Each training example has one or more inputs and the desired output, also known as a supervisory signal. In the mathematical model, each training example is represented by an array or vector, sometimes called a feature vector, and the training data is represented by a matrix.

  5. MNIST database - Wikipedia

    en.wikipedia.org/wiki/MNIST_database

    Sample images from MNIST test dataset. The MNIST database (Modified National Institute of Standards and Technology database[1]) is a large database of handwritten digits that is commonly used for training various image processing systems. [2][3] The database is also widely used for training and testing in the field of machine learning. [4][5 ...

  6. Electronic health record - Wikipedia

    en.wikipedia.org/wiki/Electronic_health_record

    The benefits of electronic records in ambulances include: patient data sharing, injury/illness prevention, better training for paramedics, review of clinical standards, better research options for pre-hospital care and design of future treatment options, data based outcome improvement, and clinical decision support. [62]

  7. Supervised learning - Wikipedia

    en.wikipedia.org/wiki/Supervised_learning

    Supervised learning. Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as a human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data to expected output values. [ 1 ]