Model to Meaning: Models with R by Vincent Arel-Bundock (.ePUB)+
File Size: 12.5 MB
Model to Meaning: How to Interpret Statistical Models with R and Python by Vincent Arel-Bundock
Requirements: .ePUB, .PDF reader, 12.5 MB
Overview: Our world is complex. To make sense of it, data analysts routinely fit sophisticated statistical or Machine Learning models. Interpreting the results produced by such models can be challenging, and researchers often struggle to communicate their findings to colleagues and stakeholders. Model to Meaning is a book designed to bridge that gap. It is a practical guide for anyone who needs to translate model outputs into accurate insights that are accessible to a wide audience. To address this challenge, this book introduces a free and open source software package, marginaleffects, which provides a single point of entry to interpret results from over 100 classes of models in R and Python. This package simplifies the interpretation process by offering a consistent and powerful user interface, reducing the need for customized code, and minimizing the risk of errors. Written for data scientists, researchers, and students, the book speaks to newcomers seeking practical skills, and to experienced analysts who are ready to adopt new tools and rethink entrenched habits. It offers useful ideas, concrete workflows, powerful software, and detailed case studies, presented using real-world data and code examples.
Genre: Non-Fiction > Tech & Devices
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