This git is for those who have concern about serving your machine learning model to production.

The tutorial will show you how to deploy your Tensorflow (Keras) model (specifically ResNet50 pretrained on Imagenet) using:

• RestAPI + Redis
• RestAPI + nginx + uwsgi
• FastAPI + Docker
• RestAPI + Kubernetes + Docker
• Tensorflow Serving

Note: This git is the my collected knowledge during my on-going journey to this interesting part of Machine Learning, so there will be some mistakes or misunderstanding. For those who detect any faults, send me a pull request and contribute!

Each method will be in each different folder with its corresponding Readme file.

Those methods are what I found on the internet with a thorough check and run test on my Mac. Things maybe different on each computer and operation system.

If you hit any problem when you try to run any of those methods, leave a issue and I will get back shortly.