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FastAPI is a high-performance web framework for building HTTP-based service APIs in Python 3.8+. [3] It uses Pydantic and type hints to validate, serialize and deserialize data. FastAPI also automatically generates OpenAPI documentation for APIs built with it. [4] It was first released in 2018.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Data type validation is customarily carried out on one or more simple data fields. The simplest kind of data type validation verifies that the individual characters provided through user input are consistent with the expected characters of one or more known primitive data types as defined in a programming language or data storage and retrieval ...
The Enthought Tool Suite open source software projects include: [6] Traits: A manifest type definition library for Python that provides initialization, validation, delegation, notification, and visualization. The Traits package is the foundation of the Enthought Tool Suite, underlying almost all other packages.
OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms.
For example, the property sh:resultMessage is designed to communicate additional textual details to users, including recommendations on how data may be fixed to address to validation result. In cases where a constraint does not have any values for sh:message in the shapes graph the SHACL processor may automatically generate other values for sh ...
Python library for the manipulation and storage of a wide range of geoscientific data (points, curve, surface, 2D and 3D grids) in geoh5 file format, natively supported by Geoscience ANALYST free 3D viewer Mira Geoscience Ltd. LPGL 3.0 Cross-platform: Python: Documentation and tutorials fully available in ReadTheDocs: geoapps repository [24]
KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.