outline.md

Outline of the Workshop

Session 1: Introduction and Concepts

• Approach for building ML products
• Problem definition and dataset
• Build your first ML Model (Part 1)

Session 2: Build a Simple ML Service

• Build your first ML Model (Part 2)
• Concept of ML Service
• Deploy your first ML Service - localhost API

Session 3: Build & Evaluate ML Models

• Feature Engineering
• Build your second ML model
• ML model evaluation
  • Accuracy metrics
  • Cross Validation

Session 4: Practice Session

• Practice problem overview and data
• Build your ML Model
• Build your API

Session 5: Build a Simple Dashboard

• Concept of Dashboard design
• Create your first dashboard
• Integrate ML model API with dashboard

Session 6: Deploy to cloud

• Get started with cloud server setup
• Deploy your ML service as cloud API
• Deploy your dashboard as cloud service

Session 7: Repeatable ML as a Service

• Build data pipelines
• Update model, API and dashboard
• Schedule ML as as Service process

Session 8: Practice Session & Wrap-up

• Deploy on cloud - dashboard and API
• Best practices and challenges in building ML service
• Where to go from here