Building Ensembles with Scikit-Learn and PyTorch (8.2)

This video examines your model's decision-making with our in-depth exploration of feature importance ranking, particularly focusing on the power of perturbation ranking. In this video, we don't just stop at understanding individual models; we also delve into the fascinating realm of ensemble modeling, merging the strengths of both PyTorch and ScikitLearn. By combining these diverse frameworks, we aim to achieve robust and accurate predictions that stand strong even in the face of complex data landscapes. Whether you're an aspiring data scientist or a seasoned machine learning enthusiast, this video is your gateway to leveraging the combined potential of PyTorch and ScikitLearn while also understanding the heart of your model's decisions.

Code for This Video:
https://github.com/jeffheaton/app_dee...

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#FeatureImportance #PerturbationRanking #EnsembleModeling #PyTorch #ScikitLearn #MachineLearning #ModelDecisions #DataScienceInsights #AdvancedML #ModelInterpretability