Blog posts about using Google Cloud Platform; mostly ML-related. Earlier posts are here.

Posts

• Use Vertex Pipelines to build an AutoML Classification end-to-end workflow

  how you can use Vertex Pipelines to build an end-to-end ML workflow for training a custom model using AutoML

  Jun 22, 2021

• Event-triggered Kubeflow Pipeline runs, and using TFDV to detect data drift

  how to set up event-triggered Kubeflow Pipelines runs, and use TFDV to detect data drift

  Feb 26, 2021

• Keras Tuner KFP example, part II— creating a lightweight component for metrics evaluation

  how to create a Kubeflow Pipelines component from a python function, and define and deploy pipelines from a notebook

  Oct 26, 2020

• Running a distributed Keras HP Tuning search using Kubeflow Pipelines

  How to use Kubeflow Pipelines to support HP Tuning using the Keras Tuner

  Oct 19, 2020

• Training an AutoML Tables model with BigQuery ML

  How to use BigQuery ML to train an AutoML Tables model

  Jul 14, 2020

• Using Google Cloud Functions to support event-based triggering of Cloud AI Platform Pipelines

  This post shows how you can run a Cloud AI Platform Pipeline from a Google Cloud Function, providing a way for Pipeline runs to be triggered by events.

  May 12, 2020

• Creating an AutoML Tables end-to-end workflow on Cloud AI Platform Pipelines

  An overview of new AutoML Tables features, via a Cloud AI Platform Pipelines example showing an end-to-end workflow

  Apr 22, 2020

• Getting explanations for AutoML Tables predictions

  How to use the AutoML Tables client libraries to create a dataset; train a custom model; deploy the model; and use the model to make predictions and get explainations about the prediction result.

  Apr 17, 2020