AWS Discovery Day: Machine Learning Basics

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