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Interpreting Machine Learning Models: A Hands-On Guide


Understanding Model Decisions for Trustworthy Machine Learning Solutions

Interpreting models is crucial because machine learning alone does not offer a complete solution. The complex issues addressed with these models can’t be solved with traditional software development due to unknowns within the problem space. By clarifying a model’s decisions, we can bridge gaps in our understanding and build trust in the AI systems we develop. In this session, we will explore the importance of model interpretation and cover methods such as feature importance, feature summary, and local explanations.

Serg Masis
Serg Masis

Data Scientist and Author

Serg Masis is a data scientist in agriculture with a lengthy background in entrepreneurship and web/app development, and the author of the bestselling book “Interpretable Machine Learning with Python”, the second edition soon to be released. Passionate about machine learning interpretability, responsible AI, behavioral economics, and causal inference.

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