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Overview — Machine Learning Zoomcamp Module 10

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mlz-module-10

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same use case as in the session before: classifying images of clothes
using tensorflow serving, written in C++, with focus on inference
gRPC binary protocol
deploying to kubernetes
1st component: gateway (download image, resize, turn into numpy array - computationally not expensive - can be done with CPU)
2nd component: model (matrix multiplications - computationally expensive - thus use GPU)
scaling the two components independently: i.e. 5 gateways handing images to 1 model
two components in two different docker container (lesson four)
kubernetes main concepts (lesson five)
running kubernetes on your local machine (lesson six)
deploy the two services to kubernetes (lesson seven)
move from local to cloud (lesson eight)

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