Discovery Day- Machine Learning Basics (AWSDD-MLB) – Outline

Detailed Course Outline

Section 1: Machine learning basics
  • Classical programming vs. machine learning approach
  • What is a model?
  • Algorithm features, weights, and outputs
  • Machine learning algorithm categories
  • Supervised algorithms
  • Unsupervised algorithms
  • Reinforcement learning
Section 2: What is deep learning?
  • How does deep learning work?
  • How deep learning is different
Section 3: The Machine Learning Pipeline
  • Overview
  • Business problem
  • Data collection and integration
  • Data processing and visualization
  • Feature engineering
  • Model training and tuning
  • Model evaluation
  • Model deployment
Section 4: What are my next steps?
  • Resources to continue learning