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Udacity

Developing your First ML Workflow

via Udacity

Overview

This course discusses how to use AWS services to train a model, deploy a model, and how to use AWS Lambda Functions, Step Functions to compose your model and services into an event-driven application.

Syllabus

  • Introduction to Developing ML Workflows
    • This lesson gives an introduction to the course, including prerequisites, final project, stakeholders, and tools & environment.
  • SageMaker Essentials
    • This lesson will go over SageMaker essential services such as training jobs, endpoints, batch transforms, and processing jobs.
  • Designing Your First Workflow
    • This lesson will discuss machine learning workflows and AWS tools such as Lambda, Step Function for building a workflow.
  • Monitoring a ML Workflow
    • This lesson will go over monitoring a machine learning workflow and some useful services within AWS to help you monitoring the healthy of data and machine learning models.
  • Project: Build a ML Workflow For Scones Unlimited On Amazon SageMaker
    • In the project, you will build and ship an image classification model with AWS SageMaker for Scones Unlimited, a scone-delivery-focused logistic company.

Taught by

Charles Landau and Joseph Nicolls

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