MLOps Coffee Sessions #1: Serving Models with Kubeflow

MLOps 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 is, 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://join.slack.com/t/mlops-community/shared_invite/zt-391hcpnl-aSwNf_X5RyYSh40MiRe9Lw
Follow 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/

Episode source