Ref: https://www.udemy.com/course/aws-ai-practitioner-certified/learn/lecture/44887789

• Contents:

JumpStart

• 🔧 ML Hub with many pre-trained models and pre-built solutions
  • Foundation Models (FMs), Computer Vision (CV) models and Natural Language Processing (NLP) models
  • Examples: HuggingFace, Databricks, Meta…
    • 💡 Bigger selection and variety than Amazon Bedrock
• Models deployed directly on SageMaker
  • full control of deployment options
• Models can be fully customized for your data and use-case
• Two options
  1. Choose a model from ML hub and customize it
  2. Pre-built ML solutions for
     • Demand forecasting
     • Credit rate prediction
     • Fraud detection
     • Computer Vision

Canvas

• 🔧 Build ML models using a visual interface (no code)
  • Access to ready-to-use models from Bedrock or JumpStart
  • Build your own custom model using AutoML powered by SageMaker Autopilot
  • Leverage Data Wrangler for data preparation
• Ready-to-use models from Amazon Rekognition, Amazon Comprehend, Amazon Textract
  • Makes it easy to build a full ML pipeline without writing code and leveraging various AWS AI Services

MLFlow on Amazon SageMaker

• 🔧 MLFlow: open-source tool which helps ML teams manage the entire ML lifecycle
  • ‼️ Independent from SageMaker!!
    • …But fully integrated into SageMakerStudio!
• SageMaker Studio can launch MLFlow Tracking Servers with a few clicks
  • used to track runs and experiments