Code-Alongs
Code-Alongs are live experiences taught by our expert instructors designed to prepare you for concepts found in the sprint challenges. They're your opportunity to work on complex job-ready problems in a live and engaging environment.
Code-Along 1: Data Wrangling and Encoding
Overview
In this Code-Along session, you'll learn essential data preparation techniques for tree-based models. We'll focus on handling categorical data and implementing proper encoding strategies that work well with decision trees and random forests.
Key Topics
- Handling missing values in categorical and numerical data
- Identifying and encoding high-cardinality categorical features
- Implementing ordinal encoding for tree-based models
- Feature selection and engineering for tree-based algorithms
Resources
Code-Along 2: Model Tuning
Overview
In this Code-Along session, you'll learn techniques for optimizing tree-based models to achieve better performance. We'll explore hyperparameter tuning, cross-validation, and model evaluation strategies specific to random forests.
Key Topics
- Identifying key hyperparameters for tree-based models
- Implementing grid search and random search for hyperparameter optimization
- Cross-validation strategies for reliable model evaluation
- Balancing model complexity against performance
- Interpreting and visualizing model performance metrics