Learner, Practitioner & Teacher
Artificial Intelligence (AI) has come a long way—from conceptual frameworks to real-world breakthroughs powering tools like ChatGPT. This post walks through the significant milestones in the journey of AI, highlighting how decades of research, setbacks, and innovation have led us
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There are several types of feature importance methods that can be used to explain how a machine learning model is making its predictions. Here are some of the most common types: Permutation Importance: This method measures the importance of each
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Partial dependence plots (PDP) are a type of model-agnostic XAI technique that allows us to visualize the relationship between an input feature and the model’s output. PDPs show how the predicted outcome changes as we vary the values of a
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SHAP (SHapley Additive explanations) is another popular method for explaining the predictions of machine learning models. In this blog post, we will explore the SHAP technique, how it works, and its application in healthcare using a use case. What
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LIME (Local Interpretable Model-agnostic Explanations) is a popular method for explaining the predictions of machine learning models, especially black-box models. In this blog post, we will explore the LIME technique, how it works, and its application in healthcare using a
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