Day 30 Part 2: Visualizations Generated, Limitations Page Done, Feature Engineering Table Complete

1. 1Generate visualizations from trained model artifacts using Python
2. 2Create a limitations page to document potential issues with the model
3. 3Build a feature engineering table to track and compare different features
4. 4Run exploratory data analysis to identify key features like hour_of_day
5. 5Configure visualization tools to effectively communicate model insights

Data scientists and analysts can benefit from this lesson to improve their visualization and feature engineering skills, while working with machine learning models

💡 Visualizations can reveal surprising insights, such as the importance of hour_of_day, and help identify model limitations

📊 Generate visualizations from trained models and track feature engineering limitations