Vision analytics solution using Dataflow and Vision AI

Google BigQuery Tutorial

Try BigQueryML when it was rolled out. I used this repository for study group.

Présentation au DAMM de novembre 2022 par Sébastien Brodeur et Desjardins. Montre comment utiliser BigQuery ML afin de détecter des anomalies dans Google Analytics 4 (nécessite que les données de GA4 soient exportées dans BigQuery déjà.)

In this project, I developed a completed Vertex and Kubeflow pipelines SDK to build and deploy an AutoML / BigQuery ML regression model for online predictions. Using this ML Pipeline, I was able to develop, deploy, and manage the production ML lifecycle efficiently and reliably.

Build a data pipeline on Google Cloud using an event-driven architecture, leveraging GCS, Cloud Run functions, and BigQuery. Explore both VM and Composer options for Airflow management, and utilize Logging & Monitoring for pipeline health. Discover how SQL-based BigQuery ML can be used for initial ML implementation in specific scenarios.

Learning, quizzes and practical lab works of Machine Learning course from Google Cloud on Coursera platform.

Project contains a flask app that queries google big query storage (holds two arima models and etl of NYT Covid19 dataset) and returns latest cases/deaths stats for US and territories, along with prediction for cases/deaths 30 days out.

Predicting the Fare on a Billion Taxi Trips with BigQuery. How long time does it take and how much does it cost to analyse and train a model on a billion taxi trips in the cloud?

Automatic Anomaly Decetor