Contains code and slides for our talk at Cloud Next 2022: Better Hardware Provisioning for ML Experiments on GCP.
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Updated
Dec 15, 2023 - HCL
Contains code and slides for our talk at Cloud Next 2022: Better Hardware Provisioning for ML Experiments on GCP.
Harness RAG CI/CD Pipeline - A Terraform implementation for deploying and managing a Retrieval-Augmented Generation (RAG) pipeline using Harness CI/CD platform and Google Cloud services (Cloud Run, Vertex AI).
A tutorial to deploy and use AI Runtime Security on Google Cloud.
A Vertex AI Search for Media demo project, exporting data from The Movie Database API, ingesting that data into BigQuery ready for Dataform to transform the data for import into Vertex AI Search for Media.
A lightweight, cloud-native ML/AI experiment pipeline for GCP using Terraform, Vertex AI, and Kubeflow Pipelines. Automates infrastructure provisioning for experiment tracking, model training, and deployment with monitoring and CI/CD integration.
Terraform module for Google Gemini/Vertex AI platform with endpoints, model deployments, and feature store
Real time adaptive learning platform. With career builder support
Use Bigquery Machine Learning (BQML) to apply advertising techniques
GCP Vertex AI Terraform module with Feature Store, Endpoints, Workbench, and Tensorboard
🌐 Deploy comprehensive data discovery systems on Google Cloud Platform with this production-ready Terraform infrastructure template.
Production-ready Terraform infrastructure for data discovery systems on Google Cloud Platform
Terraform module for Vertex AI Agents with Dialogflow CX, intents, flows, and webhooks
Enterprise-grade Multi-Cloud Architecture Portfolio featuring AWS, Azure, and GCP. Includes end-to-end data engineering pipelines, data lake & warehouse design, ML platform (Vertex AI), Terraform IaC, security architecture, and full operations documentation. Built as a real-world case study for cloud architect roles.
GenAI data pipeline that performs data preparation, management and performance evaluation tasks for RAG systems using SQL as the primary development language. Please feel free to use this as a starting point for your own projects.
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