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The Accessibility Developer Guide is a resource for designing and implementing fully accessible websites. Its contents are based strictly on the W3C's Web Content Accessibility Guidelines (WCAG 2.1), and it aims to provide best practices on designing, implementing and testing websites with accessibility in mind. It includes knowledge and examples sections covering topics such as headings, dialogs, skip links, accordions and tables.
Affixes.org is an educational website that serves as a dictionary of English prefixes and suffixes. It contains more than 1,250 entries illustrated by approximately 10,000 examples, with all entries defined and explained. The content is based on Michael Quinion’s Oxford University Press book Ologies and Isms: Word Beginnings and Endings, updated with new entries. The site has no advertisements, and relies on visitor donations via secure PayPal payments to cover running costs.
A review site for AI presentation makers, presenting examples and in-depth reviews of more than 20 tools for work and school use, with recommendations for PowerPoint and creative presentations. It also covers Plus AI, an add-in for PowerPoint that creates new slide decks, edits existing presentations, or reformats slides using AI.
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A reference site collecting rules of basic algebra with explanations and examples for each equation. It covers rules for arithmetic, exponents and radicals, stating that these simple rules can be used to solve most basic algebra problems.
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AnimeOutline provides anime and manga style drawing tutorials and tips for beginners. Its step-by-step guides cover subjects such as eyes, faces, hair, bodies and clothes, and feature original artwork as examples. The site also offers related drawing advice and lessons on overall drawing methods.
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This page introduces the Mastodon REST API, which provides access to Mastodon data over HTTP with JSON payloads. It explains REST concepts, HTTP request and response methods such as GET, POST, PUT, PATCH and DELETE, and how to provide parameters via query strings, form data or JSON, using cURL examples.
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astroML is a Python module for machine learning and data mining built on numpy, scipy, scikit-learn, matplotlib and astropy, distributed under the 3-clause BSD license. It provides statistical and machine learning routines for analyzing astronomical data, loaders for open astronomical datasets, and examples of analyzing and visualizing datasets. The project was started in 2012 to accompany a textbook on statistics, data mining and machine learning in astronomy.
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