This week was all about Decision Trees &amp; Ensemble Learning — essential techniques in machine learning that help drive decisions in fields like finance, healthcare, and beyond. Here’s what we covered:
🔹 Credit Risk Scoring Project: Developing models to assess risk in loan applications.
🔹 Data Cleaning and Preparation: Ensuring data quality for robust models.
🔹 Decision Trees &amp; Learning Algorithm: Understanding how trees make decisions, one split at a time.
🔹 Parameter Tuning: Finding the right settings for optimal performance.
🔹 Ensemble Learning - Random Forest, Gradient Boosting, and XGBoost: Combining multiple models to improve accuracy and resilience.
Here’s my homework for the week: <a href="https://github.com/RuiFSP/ml-zoomcamp/blob/main/06-trees/homework06/homework06.ipynb" target="_blank" rel="noopener nofollow">https://github.com/RuiFSP/ml-zoomcamp/blob/main/06-trees/homework06/homework06.ipynb</a>
Excited to continue the journey in Week 7! 💪

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🚀 Completed Week 6 of MLZoomcamp! 🎉