使用Flask部署机器学习模型
Introduction A lot of Machine Learning (ML) projects, amateur and professional, start with an aplomb. The early excitement with working on the dataset, answering the obvious & not so obvious questions & presenting the results are what everyone of us works for. There are compliments thrown around and talks about going to the next step -- that's when the question arises, How? The usual suspects are making dashboards and providing insights. But mostly, the real use of your Machine Learning model lies in being at the heart of a product -- that maybe a small component of an automated mailer system