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Diving into Implementation

Lesson 4/8 | Study Time: 60 Min
Course: Explainable AI (XAI)

Census Income Dataset

Also known as "Adult" dataset.

It contains weighted census data extracted from the 1994 and 1995 Current Population Surveys conducted by the U.S. Census Bureau.

OBJECTIVE: Predict whether income exceeds $50K/yr based on census data.

This is a binary classification problem.

Notebook: https://colab.research.google.com/drive/1AKFQcXpfg4hdFWx_dfE2sbPtmPWYmbGf?usp=sharing

Let's implement SHAP and see how we can derive some interesting inferences through beautiful visualizations.

PS. Some visualizations are omitted on web so it's better to open the notebook in Google Colab or Jupyter Notebook.

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Class Sessions

1- The Importance of Human Interpretable Machine Learning 2- Model Interpretation Strategies 3- SHAP 4- Diving into Implementation 5- What other tools exist? 6- The Future of Interpretability 7- Notebooks 8- Assignment

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