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How to Deploy ML Models in Production with BentoML

In this video, you can learn how to deploy Machine Learning models into production using BentoML. I explain how to install BentoML, how to save ML models into BentoML's local store, how to create a BentoML service, how to build a bento, and how to containerise a bento with Docker. I also send requests to the BentoML service to receive back inferences. Check code: https://github.com/musikalkemist/mlde... ================= Join The Sound Of AI Slack community: https://valeriovelardo.com/the-sound-... Interested in hiring me as a consultant/freelancer? https://valeriovelardo.com/ Connect with Valerio on Linkedin:   / valeriovelardo   Follow Valerio on Facebook:   / thesoundofai   Follow Valerio on Twitter:   / musikalkemist​   ================= Content 0:00 Intro 0:19 BentoML deployment steps 1:03 Installing BentoML and other requirements 2:11 Training a simple ConvNet model on MNIST 5:52 Saving Keras model to BentoML local store 10:26 Creating BentoML service 15:28 Sending requests to BentoML service 22:06 Creating a bento 25:46 Serving a model through a bento 28:25 Dockerise a bento 30:46 Run BentoML service via Docker 32:41 Deployment options: Kubernetes + Cloud 33:43 Outro