In Class Tutorials / Demos for GCP (and AWS)

Tutorial 1: Create Simple Translate App - No Docker, No Pipenv

Tutorial 2: Create Simple Translate App with Pipenv, No Docker

Tutorial 3: Create Simple Translate App with Docker, Push Image to Docker Hub

Tutorial 4: Run App in VM using Docker

Tutorial 5: Mega Pipeline App

Tutorial 5B: Mega Pipeline App with Flexible Workflow

Tutorial 6: LLM-RAG

  • Lecture: L09
  • Description: Building a RAG System with Vector DB and LLM
  • GCP GitHub URL: LLM-1

Tutorial 7: LLM-Agents

  • Lecture: L10
  • Description: LLM Agents with Phidata (Notebook)
  • Colab Notebook: LLM-Agents

Tutorial 8: LLM-Agents

Tutorial 9: LLM-Fine Tuning

Tutorial 10: Model Compression and Distillation

  • Lecture: []
  • Description: Model Compression and Distillation
  • Colab Notebook: [Model Compression and Distillation]

Tutorial 11: Experiment Tracking

Tutorial 12: Advanced Workflow: Serveless Model Training with Vertex AI

Tutorial 13: Cloud Function and Cloud Run

Tutorial 14: Label Studio

  • Lecture: 13b
  • Description: Learn how to use Label Studio for data labeling.
  • GitHub URL: Label Studio [GCP and AWS]

Tutorial 15: Data Versioning

  • Lecture: 13b
  • Description: Learn about versioning practices in development. Particularly, how to use DVC for data versioning.
  • GCP GitHub URL: DVC

Tutorial 16: Model Deployment using Vertex AI

Tutorial 17: ML Workflow

  • Lecture: L14
  • Description: Vertex AI ML Workflow for pipeline. Data Processing, data collection, model training, model deployment.
  • GCP GitHub URL: ML Workflow

Tutorial 18: Frontend

Tutorial 19: Frontend Simple

Tutorial 20: Frontend React

Tutorial 21: Frontend

Tutorial 22: App Template

Tutorial 23: CI/CD with GitHub Actions and other tools

  • Lecture: L17
  • Description: CI/CD
  • GCP GitHub URL: CI/CD

Tutorial 24: Deployment of the full app to GCP

Tutorial 25: Continuous Integration and Continuous Deployment