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Pe YEO găsești Causal Inference in Python: Applying de la Matheus Facure, în categoria Business & Economics.
Indiferent de nevoile tale, Causal Inference in Python: Applying Causal Inference in the Tech Industry - Matheus Facure din categoria Business & Economics îți poate aduce un echilibru perfect între calitate și preț, cu avantaje practice și moderne.
Preț: 446.35 Lei
Caracteristicile produsului Causal Inference in Python: Applying
- Brand: Matheus Facure
- Categoria: Business & Economics
- Magazin: libris.ro
- Ultima actualizare: 07-04-2025 02:10:02
Comandă Causal Inference in Python: Applying Online, Simplu și Rapid
Prin intermediul platformei YEO, poți comanda Causal Inference in Python: Applying de la libris.ro rapid și în siguranță. Bucură-te de o experiență de cumpărături online optimizată și descoperă cele mai bune oferte actualizate constant.
Descriere magazin:
How many buyers will an additional dollar of online marketing bring in? Which customers will only buy when given a discount coupon? How do you establish an optimal pricing strategy? The best way to determine how the levers at our disposal affect the business metrics we want to drive is through causal inference. In this book, author
Matheus Facure, senior data scientist at Nubank, explains the largely untapped potential of causal inference for estimating impacts and effects. Managers, data scientists, and business analysts will learn classical causal inference methods like randomized control trials (A/B tests), linear regression, propensity score, synthetic controls, and difference-in-differences. Each method is accompanied by an application in the industry to serve as a grounding example. With this book, you will: Learn how to use basic concepts of causal inference Frame a business problem as a causal inference problem Understand how bias gets in the way of causal inference Learn how causal effects can differ from person to person Use repeated observations of the same customers across time to adjust for biases Understand how causal effects differ across geographic locations Examine noncompliance bias and effect dilution