Speaker "Elvin Zhu" Details Back



From Concept to Production: Template for the Entire ML Journey


From Concept to Production: Template for the Entire ML Journey
We created a template in python for the entire ML journey from concept to production. The workshop offers a 2 part hands-on tutorial. Each part will be for 4 hours.
Part 1 starts with an example use case. It builds the ML components such as data prep, model hyper train, model train, model deploy and online/batch predict. These components are unit tested in a python notebook. 
Part 2 will show how to deploy these components in a Kubeflow pipeline with orchestration for training and prediction. The entire end to end ML pipeline is now ready for deployment.
At the end of this tutorial you will have hands-on experience building a model from concept to a final production-ready ML pipeline. The tutorial will be implemented on the Google Cloud Platform. Models can include xgboost, tensorflow and scikit learn models.



AI Engineer/Software Developer in Google with years of experiences in both industry and academia, empowering enterprises to transform their business using AI by developing ML models and pipelines on GCP. Ph.D. in Imaging Science from Rochester Institute of Technology.