Explainable Ai With Python, Paperback by Gianfagna, Leonida; Di Cecco, Antoni…
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In this post, we will explore the book “Explainable AI with Python” written by Gianfagna, Leonida and Di Cecco, Antoni.
This comprehensive guide covers the fundamentals of Explainable AI (XAI) and how it can be implemented using Python. The book provides a step-by-step approach to developing interpretable AI models, allowing users to understand the reasoning behind the decisions made by machine learning algorithms.
Topics covered in the book include techniques such as LIME (Local Interpretable Model-agnostic Explanations), SHAP (SHapley Additive exPlanations), and feature importance analysis. Readers will learn how to visualize and interpret model predictions, making AI more transparent and trustworthy.
Whether you are a data scientist, machine learning engineer, or AI enthusiast, “Explainable AI with Python” is a valuable resource for anyone looking to delve deeper into the world of interpretable AI. Get your hands on a copy today and unlock the power of explainability in AI.
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