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Causal Inference for Data Science

Causal Inference for Data Science

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Description
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.
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
392
Release Date:
2024-11-26
Publication Date:
2025-01-21
Publisher:
Manning Publications
Languages:
Original: English
ISBN10:
1633439658
ISBN13:
9781633439658
GPSR Manufacturer Reference:
[email protected]
Weight:
664 g
Height:
187 cm
Width:
234 cm
Thickness:
22 cm
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