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Explainable AI (XAI) is a rapidly growing field of machine learning that focuses on providing explanations for the decisions and predictions made by artificial intelligence models. Recent research by IBM has shown a significant shift in attitudes toward the ethical use of AI, highlighting the need for individuals and businesses to consider ethical implementation when utilizing explainable AI. This blog explores popular Python frameworks, including LIME, SHAP, ELI5, Shapash, and DALEX, for AI professionals and business owners who wish to build models and tools using state-of-the-art algorithms.