Instabooks AI (AI Author)
Mastery of Gradient Boosted Trees
Unleashing the Power of Machine Learning Algorithms
Premium AI Book - 200+ pages
Table of Contents
1. Introduction to Machine Learning- Foundations of Algorithms
- Evolution of Tree-Based Models
- GBT in the Machine Learning Landscape
2. Demystifying Gradient Boosted Trees
- The Anatomy of a Decision Tree
- Principles of Boosting
- Constructing a Gradient Boosted Model
3. Mathematical Groundwork
- Loss Functions Explained
- Gradient Descent Made Simple
- Combining Trees and Gradients
4. Hands-On Data Preprocessing
- Data Cleaning Essentials
- Feature Selection Strategies
- Engineering Informative Features
5. Fine-Tuning for Superior Performance
- Hyperparameter Optimization
- Avoiding Overfitting
- Model Validation Methods
6. Advanced Topics in GBT
- Regularization Techniques
- Handling Sparse Data
- Dealing with Imbalanced Classes
7. Popular GBT Frameworks
- Navigating XGBoost
- Getting Started with LightGBM
- An Introduction to CatBoost
8. Real-World Applications
- GBT in Financial Analysis
- Improving Healthcare with GBT
- Enhancing Retail with Predictive Analytics
9. Interpreting GBT Models
- Feature Importance and Model Insights
- Partial Dependence Plots
- SHAP Values and Interpretability
10. Research & Case Studies
- Cutting-Edge Developments
- Benchmarking GBT Performance
- Case Studies from Industry Leaders
11. Integration with Other ML Techniques
- Combining GBT with Neural Networks
- Ensemble Learning Explained
- Meta-Learning and GBT
12. Future of GBT
- GBT in the Age of AI
- Challenges and Opportunities
- The Horizon of Machine Learning
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