Serving Scikit-learn Models at Scale 

Thnaks Yufeng, helpful deployment steps.

Very Helpful, Thanks.

Hi Yufeng, I have a very basic requirement on Sklearn Pandas ML pipeline but I am not able to find any clear answer to this problem any where on the documentations. Let's say I have an Sklearn pipeline built using Pandas dataframe as input, with pandas functions as transformations etc. So obviously this pipeline will expect a pandas - dataframe during prediction. Does GCMLE already have capability to convert the key value paired JSON payload to Panda-DF via online-prediction mode ? Seems to be a very basic requirement if we talk about ML on Cloud, any pointers ?

thanks for the tut, but i have a question: where to put the input.json? i tried upload in the same bucket as model, error

Normally data scientists create and deploy models for users who are not familiar with gcloud command line interface. They do this in a web app environment, where users can go online by typing the web address and submit data files for prediction and get results. How can we do that using GCP?

Yo

DO NOT MAKE A VIDEO IN FUTURE IF YOU JUST SPEAK ON THE GENERAL STEPS WITHOUT MENTIONING "HOW TO..." PART OF THOSE STEPS. JUST A WASTAGE OF TIME....