Causal inference and discovery in python

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Demystify causal inference and casual discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental data Purchase of the print or Kindle book includes a free PDF eBook

Key Features Examine Pearlian causal concepts such as structural causal models, interventions, counterfactuals, and more Discover modern causal inference techniques for average and heterogenous treatment effect estimation Explore and leverage traditional and modern causal discovery methods Book DescriptionCausal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely statistical mindset. Causal Inference and Discovery in Python helps you unlock the potential of causality. You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python code. Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the power of cutting-edge algorithms. You’ll further explore the mechanics of how “causes leave traces” and compare the main families of causal discovery algorithms. The final chapter gives you a broad outlook into the future of causal AI where we examine challenges and opportunities and provide you with a comprehensive list of resources to learn more. By the end of this book, you will be able to build your own models for causal inference and discovery using statistical and machine learning techniques as well as perform basic project assessment. What you will learn Master the fundamental concepts of causal inference Decipher the mysteries of structural causal models Unleash the power of the 4-step causal inference process in Python Explore advanced uplift modeling techniques Unlock the secrets of modern causal discovery using Python Use causal inference for social impact and community benefit Who this book is for

This book is for machine learning engineers, researchers, and data scientists looking to extend their toolkit and explore causal machine learning. It will also help people who’ve worked with causality using other programming languages and now want to switch to Python, those who worked with traditional causal inference and want to learn about causal machine learning, and tech-savvy entrepreneurs who want to go beyond the limitations of traditional ML. You are expected to have basic knowledge of Python and Python scientific libraries along with knowledge of basic probability and statistics.

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Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more

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Causal Inference in Python

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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 causa Direct beschikbaar .. MEER INFO

Causal Inference in Python

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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 caus Uiterlijk 26 oktober in huis .. MEER INFO

Taal: en

Bindwijze: E-book

Oorspronkelijke releasedatum: 31 mei 2023

Ebook Formaat: Adobe ePub

Hoofdauteur: Aleksander Molak

Hoofduitgeverij: Packt Publishing

Lees dit ebook op: Desktop (Mac en Windows)

Lees dit ebook op: Kobo e-reader

Lees dit ebook op: Android (smartphone en tablet)

Lees dit ebook op: iOS (smartphone en tablet)

Lees dit ebook op: Windows (smartphone en tablet)

Studieboek: Nee

EAN: 9781804611739

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