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Condición: New.

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: As New. Unread book in perfect condition.

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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.

Condición: New.

Condición: As New. Unread book in perfect condition.

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.

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.