{"product_id":"machine-learning-for-causal-inference-9783031350535","title":"Machine Learning for Causal Inference","description":"\u003cp\u003e • Author(s): Sheng Li | Zhixuan Chu\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Artificial Intelligence - General\u003c\/p\u003e\u003cp\u003eOverview of the Book.- Causal Inference Preliminary.- Causal Effect Estimation: Basic Methodologies.- Causal Inference on Graphs.- Causal Effect Estimation: Recent Progress, Challenges, and Opportunities.- Fair Machine Learning Through the Lens of Causality.- Causal Explainable AI.- Causal Domain Generalization.- Causal Inference and Natural Language Processing.- Causal Inference and Recommendations.- Causality Encourage the Identifiability of Instance-Dependent Label Noise.- Causal Interventional Time Series Forecasting on Multi-horizon and Multi-series Data.- Continual Causal Effect Estimation.- Summary.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Paperback","offer_id":47658114252951,"sku":"9783031350535","price":11017.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783031350535.webp?v=1775817108","url":"https:\/\/atlanticbooks.com\/products\/machine-learning-for-causal-inference-9783031350535","provider":"Atlantic Books","version":"1.0","type":"link"}