Free Download Antonio Vargas, "Time's Causal Power Proclus and the Natural Theology of Time "
English | ISBN: 9004466673 | 2021 | 240 pages | PDF | 24 MB
In Time's Causal Power, Antonio Vargas explains how Proclus (412-485 C.E.) developed the unique theory that time is a cause and a god, the world's first unmoved mover by addressing Aristotle's criticisms of Plato's claim that time is a change.

Causal Factor Investing Can Factor Investing Become Scientific by Marcos M Lopez de Prado PDF | 2.77 MB
N/A | 92 Pages

Title: Causal Factor Investing
Author: Marcos M. López de Prado
Year: N/A

Free Download Machine Learning for Causal Inference
English | 2023 | ISBN: 3031350502 | 544 Pages | PDF EPUB (True) | 27 MB
This book provides a deep understanding of the relationship between machine learning and causal inference. It covers a broad range of topics, starting with the preliminary foundations of causal inference, which include basic definitions, illustrative examples, and assumptions. It then delves into the different types of classical causal inference methods, such as matching, weighting, tree-based models, and more. Additionally, the book explores how machine learning can be used for causal effect estimation based on representation learning and graph learning. The contribution of causal inference in creating trustworthy machine learning systems to accomplish diversity, non-discrimination and fairness, transparency and explainability, generalization and robustness, and more is also discussed. The book also provides practical applications of causal inference in various domains such as natural language processing, recommender systems, computer vision, time series forecasting, and continual learning. Each chapter of the book is written by leading researchers in their respective fields.

Free Download Causal Inference for Data Science (MEAP V07)
English | 2023 | ISBN: 9781633439658 | 359 Pages | PDF EPUB | 9 MB
It's possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You'll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions.

Li S Machine Learning for Causal Inference 2023 | 11.7 MB
N/A | 302 Pages

Title: Machine Learning for Causal Inference
Author: N/A
Year: N/A

Free Download Experimental and Quasi-Experimental Designs for Generalized Causal Inference By William R. Shadish, Thomas D. Cook, Donald T. Campbell
2002 | 646 Pages | ISBN: 0395615569 | PDF | 42 MB
This is a book for those who have already decided that identifying a dependable relationship between a cause and its effects is a high priority and who wish to consider experimental methods for doing so. Such causal relationships are of great importance in human affairs. The rewards associated with being correct in identifying causal relationships can be high, an the costs of misidentification can be tremendous. This book has two major purposes: to describe ways in which testing causal propositions can be improved in specific research projects, and to describe ways to improve generalizations about causal propositions. This long awaited successor of the original Cook/Campbell Quasi-Experimentation: Design and Analysis Issues for Field Settings represents updates in the field over the last two decades. The book covers four major topics in field experimentation:- Theoretical matters: Experimentation, causation, and validity- Quasi-experimental design: Regression discontinuity designs, interrupted time series designs, quasi-experimental designs that use both pretests and control groups, and other designs- Randomized experiments: Logic and design issues, and practical problems involving ethics, recruitment, assignment, treatment implementation, and attrition- Generalized causal inference: A grounded theory of generalized causal inference, along with methods for implementing that theory in single and multiple studies

Free Download The Oxford Handbook of Causal Reasoning (Oxford Library of Psychology) edited by Michael Waldmann
English | April 27, 2017 | ISBN: 0199399557 | True EPUB/PDF | 768 pages | 15.5/47.7 MB
Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Although causal reasoning is a component of most of our cognitive functions, it has been neglected in cognitive psychology for many decades. The Oxford Handbook of Causal Reasoning offers a state-of-the-art review of the growing field, and its contribution to the world of cognitive science.

Free Download Handbook of Matching and Weighting Adjustments for Causal Inference
English | 2023 | ISBN: 0367609525 | 634 Pages | PDF (True) | 22 MB
An observational study infers the effects caused by a treatment, policy, program, intervention, or exposure in a context in which randomized experimentation is unethical or impractical. One task in an observational study is to adjust for visible pretreatment differences between the treated and control groups. Multivariate matching and weighting are two modern forms of adjustment. This handbook provides a comprehensive survey of the most recent methods of adjustment by matching, weighting, machine learning and their combinations. Three additional chapters introduce the steps from association to causation that follow after adjustments are complete.

Causal Factors for Wetland Management and Restoration: A Concise Guide
English | 2023 | ISBN: 303121787X | 273 Pages | PDF EPUB (True) | 28 MB
This book presents 12 effective methods to manage wetlands for conservation. It offers a tool box of causal factors that can be used to protect and restore wetlands to enhance biological diversity and other functions. Each causal factor is introduced, briefly explained, and then illuminated with selected examples from around the world.

Causal Inference for Data Science (MEAP V04)
English | 2022 | ISBN: 9781633439658 | 201 Pages | PDF EPUB | 5 MB
It's possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You'll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions.