ISBN: 9781633439658 - causal inference for data science (30 resultados)

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Hardcover. Condición: new. Hardcover. When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning.In Causal Inference for Data Science you will learn how to: Model reality using causal graphsEstimate causal effects using statistical and machine learning techniquesDetermine when to use A/B tests, causal inference, and machine learningExplain and assess objectives, assumptions, risks, and limitationsDetermine if you have enough variables for your analysis It's possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You'll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions. Causal Inference for Data Science introduces data-centric techniques and methodologies you can use to estimate causal effects. The numerous insightful examples show you how to put causal inference into practice in the real world. The practical techniques presented in this unique book are accessible to anyone with intermediate data science skills and require no advanced statistics! Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Hardback. Condición: New. When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning.In Causal Inference for Data Science you will learn how to: Model reality using causal graphsEstimate causal effects using statistical and machine learning techniquesDetermine when to use A/B tests, causal inference, and machine learningExplain and assess objectives, assumptions, risks, and limitationsDetermine if you have enough variables for your analysis It's possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You'll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions. …

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Taschenbuch. Condición: Neu. Neuware - From the Back Cover: Causal Inference for Data Science introduces data-centric techniques and methodologies you can use to estimate causal effects. The book dives into the relationship between causal inference and machine learning and the limitations of both. The practical techniques presented in this unique book are accessible to anyone with intermediate data science skills and require no advanced statistics! The numerous insightful examples show you how to put causal inference into practice in the real world. You'll assess the performance of advertising platforms, choose the health treatments with the most positive impact, and learn how to approach the delicate art of product pricing from a causal inference perspective. About the reader: For data scientists, machine learning engineers, statisticians and economists who want to learn a machine learning approach to causal inference. …

Condición: New. &Uumlber den AutorAleix Ruiz de Villa is a freelance data science consultant with a PhD in mathematical analysis from the Universitat Autonoma de Barcelona. Aleix has worked in the journalism, retail, transportation and software .

Hardback. Condición: New. When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning.In Causal Inference for Data Science you will learn how to: Model reality using causal graphsEstimate causal effects using statistical and machine learning techniquesDetermine when to use A/B tests, causal inference, and machine learningExplain and assess objectives, assumptions, risks, and limitationsDetermine if you have enough variables for your analysis It's possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You'll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions. …

Hardcover. Condición: new. Hardcover. When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning.In Causal Inference for Data Science you will learn how to: Model reality using causal graphsEstimate causal effects using statistical and machine learning techniquesDetermine when to use A/B tests, causal inference, and machine learningExplain and assess objectives, assumptions, risks, and limitationsDetermine if you have enough variables for your analysis It's possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You'll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions. Causal Inference for Data Science introduces data-centric techniques and methodologies you can use to estimate causal effects. The numerous insightful examples show you how to put causal inference into practice in the real world. The practical techniques presented in this unique book are accessible to anyone with intermediate data science skills and require no advanced statistics! Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condición: Neu. Causal Inference for Data Science | Alex Ruiz de Villa | Taschenbuch | Kartoniert / Broschiert | Englisch | 2025 | Manning Publications | EAN 9781633439658 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.…

Taschenbuch. Condición: Neu. Neuware -From the Back Cover: Causal Inference for Data Science introduces data-centric techniques and methodologies you can use to estimate causal effects. The book dives into the relationship between causal inference and machine learning and the limitations of both. The practical techniques presented in this unique book are accessible to anyone with intermediate data science skills and require no advanced statistics! The numerous insightful examples show you how to put causal inference into practice in the real world. You'll assess the performance of advertising platforms, choose the health treatments with the most positive impact, and learn how to approach the delicate art of product pricing from a causal inference perspective. About the reader: For data scientists, machine learning engineers, statisticians and economists who want to learn a machine learning approach to causal inference. 392 pp. Englisch. …