Book Content
chapters • 27h16m total length
1. Introduction to Data Science in Python
2. Regression
3. Binary Classification
4. Multiclass Classification with RandomForest
5. Performing Your First Cluster Analysis
6. How to Assess Performance
7. The Generalization of Machine Learning Models
8. Hyperparameter Tuning
9. Interpreting a Machine Learning Model
10. Analyzing a Dataset
11. Data Preparation
12. Feature Engineering
13. Imbalanced Datasets
14. Dimensionality Reduction
15. Ensemble Learning
16. Machine Learning Pipelines
17. Automated Feature Engineering
