BentoML: Create an ML Powered Prediction Service in Minutes

After training a model, data scientists might want other members of their team including their manager to try out their model. However, their team members might have different operating systems from them and might be not familiar with their programming language. Thus, it is necessary for data scientists to containerize their model and create an intuitive API endpoint for their teammates to interact with. However, data scientists might not have all the time and skills to do all of the things above. Luckily, BentoML allows data scientists to put their models into production with ease. This presentation will show how data practitioners can containerize and share their local machine learning model with their teammates in a couple of lines of Python code