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Causal Inference in Python: Applying Causal Inference in the Tech Industry

Name: Causal Inference in Python: Applying Causal Inference in the Tech Industry
Price: 47.99 USD
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Book Synopsis: 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

Details

Unlock the ultimate power of data-driven decision making in the tech industry with Causal Inference in Python! In today's competitive landscape, it's crucial to understand the impact of every marketing dollar spent. With this book, you'll discover proven methods like randomized control trials, linear regression, and more, to accurately estimate the impact and effects of your business decisions. Whether you're a manager, data scientist, or business analyst, this book will equip you with the tools you need to make informed choices and ultimately drive success in your industry.

Leave the guesswork behind and embrace the science of causal inference. Say goodbye to assumptions and hello to tangible results. As a senior data scientist at Nubank, author Matheus Facure brings invaluable expertise to the table, ensuring that each causal inference method is backed by real-world applications. You'll gain a deeper understanding of how to frame your business challenges as causal inference problems and effectively address them for optimal results.

Beware of the bias trap! Inaccurate insights can hinder your decision-making process. Causal Inference in Python will guide you in navigating the obstacles of bias, enabling you to make objective and data-driven choices. Learn how to uncover the factors that influence individual customers, adjust for biases using repeated observations, and reveal the nuances of causal effects in different geographical locations. With this newfound knowledge, you'll be empowered to take your business to new heights.

Don't miss your chance to gain a competitive edge in the tech industry. Invest in your success today with Causal Inference in Python. Click here to grab your copy and unlock the untapped potential of causal inference!

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