Causal AIis a practical introduction to building AI models that can reason about causality. Robert Ness clear, code-first approach explains essential details of causal machine learning that are hidden in academic papers. Everything you learn can be easily and effectively applied to industry challenges, from building explainable causal models to predicting counterfactual outcomes.Publisher: Manning PublicationsAuthor(s): Robert Osazuwa NessNumber of pages: 520Publication date: 2025Dimensions: 235 x 188 x 31Cover type: Hardback