Machine Learning Model Interpretability using AzureML & Interpret-ml (Explainable Boosting Machine)

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This was a presentation at Global AI Bootcamp, Singapore. In this session, I discussed the importance of model interpretability, how to create accurate and interpretable models. I present case studies on using Explainable Boosting Machines from Interpret-ML (AzureML) to create Glassbox models without sacrificing accuracy.

Sandeep Pawar
  1. PawarBI
  2. azureml
  3. machine learning
  4. model interpretability
  5. interpret-ml
  6. explainable boosting machine
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Комментарии
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Can you please share links of the notebooks you showcased?

saumilkapadia
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Hi Sandeep, thanks for your great work. I read a lot of your articles :).
Do you have the recording or know how I can find the recording of the "Introduction to Azure ML SDK" in "Azure Saturday Hamburg 2021" event? As I know, your presentation of the same topic in Global AI bootcamp got some technical issue, so you don't have the recording for that presentation either right?

Thanks! Stay safe!

dattrieuds
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