pstrongA deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit, including SHAP, feature importance, and causal inference, to build fairer, safer, and more reliable models.strongppbrppstrongPurchase of the print or Kindle book includes a free eBook in PDF format.strongppbrppstrongKey Features strongpulliInterpret real-world data, including cardiovascular disease data and the COMPAS recidivism scoresliliBuild your interpretability toolkit with global, local, model-agnostic, and model-specific methodsliliAnalyze and extract insights from complex models from CNNs to BERT to time series modelsliulpbrppstrongBook Description strongppInterpretable Machine Learning with Python, Second Edition, brings to light the key concepts of interpreting machine learning models by analyzing real-world data, providing you with a wide range of skills and tools to decipher the results of even the most complex models.ppbrppBuild your interpretability t