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

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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.

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Hi, great job and very helpful. But, correct caption should be "Machine Learning" not "Deep Learning". Thanks for your effort.

patrickonodje
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Thanks for the tutorial, which versions of SHAP and keras are you using?

maya
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I want to run this code in my dataset but I couldn't done it. Can you help to solve it or any suggestions How can I solve it? (How Can I connect Drive) or need annotation ?

MoshfiqurRahmanAjmain
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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?

mallasudhakara
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Can you plz suggest some explainable library for time series...

VLM
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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.

abhishekjain
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Thanks a lot, for the video. very useful :)

praneethkrishna
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How much time does the whole code take to run?

tishachhabra