@adataodyssey

*NOTE*: You will now get the XAI course for free if you sign up (not the SHAP course) 
SHAP course: https://adataodyssey.com/courses/shap-with-python/ 
XAI course: https://adataodyssey.com/courses/xai-with-python/ 
Newsletter signup: https://mailchi.mp/40909011987b/signup

@manta_40

Hi Connor, thank you so much for the videos, absolutelly love SHAP. Helped me a lot when comparing why my deployed models were performing differently with production data compared to the training phase. It just sometimes bugs me that the scaling and representation, slightly changes when switching between Algorithms (RandomForest, XGBoost, LightGBM, CatBoost), which makes it difficult to directly compare the SHAP Analysis. Still I'm barelly scratching the surface, but hope to dive a little deeper with the next project. The Videos were a huge help. Might look into your course soon. Regards from Rhineland Palatinate

@chougaghil

I am very happy with your videos
For my use case, temporal series, beeswarm or violin is not helping
But the heatmap gives me a nice overview

@bazelal-shaibah111

Thank you for the nice videos. Can you share the codes of these tutorials in Python, please?

@ms.mousoomibora9526

Highly helped by your video lectures..SHAP, LIME these tools are model agnostic. Can we use the same in our own model that may contain different deep learning architectures like CNN-ANN or CNN-LSTM etc...