{"id":233,"date":"2025-01-19T11:48:34","date_gmt":"2025-01-19T11:48:34","guid":{"rendered":"https:\/\/jamesflint.net\/?page_id=233"},"modified":"2025-02-05T23:39:12","modified_gmt":"2025-02-05T23:39:12","slug":"news-classification-engine","status":"publish","type":"page","link":"https:\/\/jamesflint.net\/?page_id=233","title":{"rendered":"News Classification Engine (2018)"},"content":{"rendered":"\n
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In 2017-2018 I took the Springboard Data Science Career Track<\/a> course. I was working business news company, Curation<\/a>. <\/p>\n\n\n\n

At the time. Curation was paying a sizable team of journalists to select, summarise and tag news articles, an operation that was costly and non-scalable. I built this semantic classifier using machine learning techniques to demonstrate how the company might automate much of its editorial process, and reserve human intervention for editorial sign-off and original business insight instead of using it to perform relatively low-level text processing tasks. Several components are required in order to solve this problem. <\/p>\n\n\n\n

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