Learn how to deploy, manage, monitor, retrain, and secure models in production faster than ever before using ModelOps and (1) automated model deployment, and (2) model retraining. The hardest part of AI shouldn’t be the handoff between data science and development teams, and this talk explores ways to reduce friction in this process, and speed up and improve how you build AI-powered applications. Examples will show automated deployment of models developed by leading machine learning companies, and retraining using a Jupyter notebook.