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It is also used for the Blender user manual [10] and Python API documentation. [11] In 2010, Eric Holscher announced [12] the creation of the Read the Docs project as part of an effort to make maintenance of software documentation easier. Read the Docs automates the process of building and uploading Sphinx documentation after every commit.
Attribute values can be set-valued or atomic-valued. Set-valued attributes contain more than one atomic value. Examples are role and project. Atomic-valued attributes contain only one atomic value. Examples are clearance and sensitivity. Attributes can be compared to static values or to one another, thus enabling relation-based access control.
An ICD is the umbrella document over the system interfaces; examples of what these interface specifications should describe include: The inputs and outputs of a single system, documented in individual SIRS (Software Interface Requirements Specifications) and HIRS (Hardware Interface Requirements Specifications) documents, would fall under "The Wikipedia Interface Control Document".
Python Package Index (formerly the Python Cheese Shop) is the official directory of Python software libraries and modules; Useful Modules in the Python.org wiki; Organizations Using Python – a list of projects that make use of Python; Python.org editors – Multi-platform table of various Python editors
In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars. Face detection simply answers two question, 1. are there any human faces in the collected images or video? 2. where is the face located?
The Liberty Alliance Project was an organization formed in September 2001 to establish standards, guidelines and best practices for identity management in computer systems. It grew to more than 150 organizations, including technology vendors, consumer-facing companies, educational organizations and governments.
Project Jupyter's name is a reference to the three core programming languages supported by Jupyter, which are Julia, Python and R. Its name and logo are an homage to Galileo's discovery of the moons of Jupiter, as documented in notebooks attributed to Galileo. Jupyter is financially sponsored by NumFOCUS. [1]
Named-entity recognition (NER) (also known as (named) entity identification, entity chunking, and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.