sagemaker ML project from 0 to end

instructions how to do AWS sagemaker python logistic regression ML project from 0 to end with production for 20 predictions per second
you provide
1
train scikit learn logistic regression ML project (https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html )
2
hyperparameters tuning (some python library like optuna ) on many distributed workers in parallel
3
inference model for production
4
how to use inference model for production

main idea : I need to learn how to do ML project on sagemaker for personal use

also teach how to create test code and environment -> should be created to request these 20 predictions per second , possibly from local computer or better from another cloud service like azure , digital ocean and etc..

2 days timeline

I need to learn only sagemaker - > I am familiar with elementary python and basic machine learning models

you deliver
1
video or doc file with screen copies : step by step how to implement such a project
2
python code

some ideas
https://www.youtube.com/watch?v=Le-A72NjaWs

next 2 project will be to do the same for GCP and Azure