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Deep Learning Model Explainability Using SHAP | Explainable AI | Data Science | Machine Learning



Karndeep Singh

Video Demonstrate the use of model explainability and understanding of the importance of the features such as pixels in the case of image modeling using SHAP Framework.

Notebook Link:https://github.com/karndeepsingh/Explainable-Ai

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Connect with me on :
1. LinkedIn: https://www.linkedin.com/in/karndeepsingh/
2. Telegram Group: https://telegram.me/datascienceclubachievers
3. Github: https://www.github.com/karndeepsingh

#datascience #deeplearning #machinelearning

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10 thoughts on “Deep Learning Model Explainability Using SHAP | Explainable AI | Data Science | Machine Learning
  1. The feature values are there, i am using the decision tree to predict the label as 0 or 1. but instead the decision tree should predict the output in the range of [0,100] like score. is it possible to get this using SHAP?

  2. I saw this error – "keras is no longer supported, please use tf.keras instead. Your TensorFlow version is newer than 2.4.0 and so graph support has been removed in eager mode. See PR #1483 for discussion."
    How did you resolve this? I have built LSTM model for my sequential data and tried to explain the model using SHAP but got the same error. Please help.

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