Are you using flask or Fast API to serve your machine learning models? tf serving is a tool that allows you to bring up a model server with single command. It also allows to do model version management, loading of models dynamically. It supports features such as version labels, configurable version policy etc. In this video, I will explain you everything in a very easy language.
Code: https://github.com/codebasics/deep-learning-keras-tf-tutorial/tree/master/48_tf_serving
⭐️ Timestamps ⭐️
00:00 Introduction
00:24 What problem tf serving solves?
04:44 tf serving installation
09:23 tf serving using model_base_path
14:05 serve different versions using model config file
15:35 version labels
Deep learning playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO
Machine learning playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw
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#tfservingexample #tfservingdockerfile #tfservingvsflask #tfservingmodel #tfserving #tfservingdeeplearning #tfservingmodeldeeplearning #deeplearningtfserving #deeplearningtfservingmodel #tensorflowservingtutorial
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