English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present Afro-MNIST, a set of synthetic MNIST-style datasets for fourorthographies used in Afro-Asiatic and Niger-Congo languages: Ge`ez (Ethiopic),Vai, Osmanya, and N'Ko. These datasets serve as "drop-in" replacements forMNIST. We also describe and open-source a method for synthetic MNIST-styledataset generation from single examples of each digit. These datasets can befound at https://github.com/Daniel-Wu/AfroMNIST. We hope that MNIST-styledatasets will be developed for other numeral systems, and that these datasetsvitalize machine learning education in underrepresented nations in the researchcommunity.

Afro-MNIST: Synthetic generation of MNIST-style datasets for low-resource languages