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Colab — jupyter notebook online integrated development environment developed by google A playground allows learning about, experimenting with and sharing source code The zen of python is a collection of 19 guiding principles for writing computer programs that influence the design of the python programming language
[1] python code that aligns with these principles is often referred to as pythonic. The following table lists notable online software source code playgrounds Nlweb natural language web or nlweb was introduced by microsoft in 2025
It is an open python project designed to simplify the creation of natural language interfaces for websites
[1] it enables users to query website contents using natural language, similar to interacting with an ai assistant. Chainer is an open source deep learning framework written purely in python on top of numpy and cupy python libraries The development is led by japanese venture company preferred networks in partnership with ibm, intel, microsoft, and nvidia Is a software company based in austin, texas that develops scientific and analytic computing solutions using primarily the python programming language
It is best known for the early development and maintenance of the scipy library of mathematics, science, and engineering algorithms [3] and for its python for scientific computing distribution enthought canopy (formerly epd) [503] 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 [504] a large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms. [4][5] created by pierre raybaut [6] and released in 2009 [1][2] under the mit license, [7] since 2012 spyder has been maintained and.
There are several open source projects that provide similar data version control capabilities to dvc, [52] such as
Git lfs, dolt, nessie, and lakefs These projects vary in their fit to the different needs of data engineers and data scientists such as Scalability, supported file formats, support in tabular data and unstructured data, volume.
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