MLOps Coffee Sessions #1: Serving Models with Kubeflow

Join the Community: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTJoinIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Get the newsletter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTNewsletterMLOps coffee sessions coming at you with our primer episode talking bout KFserving!   David Aponte and Demetrios Brinkmann dive deep into what model serving is in machine learning, what different types of serving there are, what serverless means, API endpoints, streaming and batch data, and a bit of coffee vs tea banter.   ||Show Notes||  ML in Production is Hard Blog article by Nikki: http://veekaybee.github.io/2020/06/09/ml-in-prod/?utm_campaign=Data_Elixir&utm_source=Data_Elixir_289 Interactive learning platform Katacoda: https://www.katacoda.com/ Github repo used in video: https://github.com/aponte411/demos Blog on different ways to handle model serving: http://bugra.github.io/posts/2020/5/25/how-to-serve-model/  Join our Slack community: https://go.mlops.community/slackFollow us on Twitter: @mlopscommunity Sign up for the next meetup: https://zoom.us/webinar/register/WN_a_nuYR1xT86TGIB2wp9B1g  Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with David on LinkedIn: https://www.linkedin.com/in/aponteanalytics/