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Module 6: Decision Trees and Ensemble Learning — Machine Learning Zoomcamp

Lessons, materials, and key concepts for module 6 of Machine Learning Zoomcamp.

Machine Learning Zoomcamp > Module 6: Decision Trees and Ensemble Learning

6. Decision Trees and Ensemble Learning

• 6.1 Credit risk scoring project
• 6.2 Data cleaning and preparation
• 6.3 Decision trees
• 6.4 Decision tree learning algorithm
• 6.5 Decision trees parameter tuning
• 6.6 Ensemble learning and random forest
• 6.7 Gradient boosting and XGBoost
• 6.8 XGBoost parameter tuning
• 6.9 Selecting the best model
• 6.10 Summary
• 6.11 Explore more
• 6.12 Homework

Community notes

Did you take notes? You can share them here (or in each unit separately)

• Kwang Yang’s Notes
• [Alvaro Navas

Lessons

Key concepts

• Decision Trees
• Pandas
• scikit-learn
• Classification Metrics
• Gradient Boosting
• Jupyter Notebooks
• Regularization

Homework and deadlines live in the course repository: machine-learning-zoomcamp.

Other modules in this course

• Module 1: Introduction to Machine Learning
• Module 2: Machine Learning for Regression
• Module 3: Machine Learning for Classification
• Module 4: Evaluation Metrics for Classification
• Module 5: Deploying Machine Learning Models
• Module 8: Neural Networks and Deep Learning
• Module 9: Serverless Deep Learning
• Module 10: Kubernetes and TensorFlow Serving