Seamless Integration: Scaled, Balanced Predictions Meet the Original Dataset | PD Model Dev - 4
In this video, we explore the critical step of integrating scaled and balanced predictions with the original dataset. Join us as we seamlessly merge optimized predictions back into the source data, creating a robust foundation for predictive modelling.
📊 Key Topics Covered:
Integration of Scaled Predictions
Balancing Techniques Applied
Merging Predictions with Original Dataset
🌐 Series Overview:
This video is the fourth instalment of our comprehensive PD Model Development Series. Whether you're a seasoned data scientist or a beginner on the journey to predictive modelling excellence, this series equips you with essential skills for credit risk assessment.
🎓 Who is This For?
Data Scientists and Analysts
Credit Risk Modelers
Those Interested in Integration Techniques
👍 Engage With Us:
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Resources -
Developed script in the video - https://github.com/LEARNEREA/Data_Sci...
Script to understand the diff. in scores - https://github.com/LEARNEREA/Data_Sci...
Automated Pre-processing - https://github.com/LEARNEREA/Data_Sci...
Logistic saved model - https://github.com/LEARNEREA/Data_Sci...
Random Forest saved model - https://github.com/LEARNEREA/Data_Sci...
XGB saved model - https://github.com/LEARNEREA/Data_Sci...
Raw data utilised in the development - https://github.com/LEARNEREA/Data_Sci...
Raw data utilised in the development - https://github.com/LEARNEREA/Data_Sci...
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Ready to elevate your predictive modeling skills? Watch now and learn the seamless integration of scaled and balanced predictions with the original dataset!
#DataScience #PredictiveModeling #IntegrationTechniques #PDModelDevelopment #CreditRisk #DataIntegration
