shinyarah/Swahili-News-Classification

### TEAM NAME: COEUS ### TEAM MEMBERS 1. Wanjiru Kinyara 2. Ezra Mageto 3. Daniel Musili 4. Ann Mberi - TL ### DATASET The data used in this project can be found here. ### PROBLEM STATEMENT. Swahili is spoken by 100-150 million people across East Africa. In Tanzania, it is one of two national languages (the other is English) and it is the official language of instruction in all schools. News in Swahili is an important part of the media sphere in Tanzania. News contributes to education, technology, and the economic growth of a country, and news in local languages plays an important cultural role in many Africa countries. In the modern age, African languages in news and other spheres are at risk of being lost as English becomes the dominant language in online spaces. The Swahili news dataset was created to reduce the gap of using the Swahili language to create NLP technologies and help AI practitioners in Tanzania and across Africa continent to practice their NLP skills to solve different problems in organizations or societies related to Swahili language. Swahili News were collected from different websites that provide news in the Swahili language. I was able to find some websites that provide news in Swahili only and others in different languages including Swahili. ### MAIN OBJECTIVE To develop a multi-class classification model to classify news content according to their specific categories specified. #### SPECIFIC OBJECTIVES. * To classify national news as national news * To classify international news as international news * To classify business news as business news * To classify sports news as sports news * To classify entertainment news as entertainment news ### DATA UNDERSTANDING. The dataset was created for a specific task of text classification, this means each news content can be categorized into six different topics (Local news, International news , Finance news, Health news, Sports news, and Entertainment news). The dataset comes with a specified trai …