ML Examples

Short ml examples for data scientists using Google Cloud Platform (GCP).

Tasks

• Identify fraudulent transactions in a credit transaction database [code]

Methodology

The approach followed while solving the ML task adopts the following increasing levels of complexity.

Low complexity; service use

• Training and prediction (BQML)

Moderate complexity; composition of services

• Notebooks parameterizing jobs on Cloud AI Platform (CAIP)
• Traininng and Prediction using CAIP

Intermediate complexity; pipeline orchestration of services

• Notebooks parameterizing pipelines
• Traininng and Prediction using CAIP
• Pipeline orchestration using kubeflow

High complexity; automated orchestration of a CT/CD pipeline

• Pipelines as packaged software
• Custom training pipeline (kubeflow)
• Custom prediction service (cloud functions, cloud run)
• Continuous training, deployment (cloud build)