Intermediate Machine Learning

Handle missing values, non-numeric values, data leakage, and more.

• Review what you need for this course.
• Missing values happen. Be prepared for this common challenge in real datasets.
• There's a lot of non-numeric data out there. Here's how to use it for machine learning.
• A critical skill for deploying (and even testing) complex models with pre-processing.
• A better way to test your models.
• The most accurate modeling technique for structured data.
• Find and fix this problem that ruins your model in subtle ways.

• Introduction
• Missing Values
• Categorical Variables
• Pipelines
• Cross-Validation
• XGBoost
• Data Leakage