Abstract:
Fake news is characterized as a story made up with the deliberate of misdirecting or deluding. In
this article we display the arrangement to the fake news location action utilizing Profound
Learning structures for the Amharic dialect. Gartner's investigate [21] predicts that "By 2022,
most individuals in developed economies will devour more untrue data than genuine data." The
exponential increment within the generation and dispersion of wrong news in Ethiopia and
within the world presents the quick have to be consequently tag and identify such bent news
articles. In any case, programmed discovery of fake news may be a troublesome assignment to
achieve because it requires the demonstrate to get it the subtleties of common dialect. In
expansion, most existing fake news discovery models treat the issue in address as a twofold
classification movement, which limits the model's capacity to get it how related or irrelevant
detailed news is compared to genuine news. To address these gaps, we present neural network
architecture to accurately predict the position between a given pair of titles and the body of the
article in Amharic language. Our model able to achieve 95.21% accuracy on test data
