Welcome to our book review site www.go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Causality
Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections and statistical associations. The book will facilitate the incorporation of causal analysis as an integral part of the standard curriculum in statistics, business, epidemiology, social science and economics. Causality will be of interest to professionals and students in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences.
Summary of Judea Pearl's The Book of Why by Milkyway Media
The Book of Why: The New Science of Cause and Effect (2018) explores an underutilized science called causal inference, a tactic which mimics humanity’s natural ability to determine a cause by observing an effect. By employing causal inference, scientists are able to mathematically determine the causes and effects of a given phenomenon... Purchase this in-depth summary to learn more.
The Book of Why
A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
Summary of Judea Pearl & Dana Mackenzie's The Book of Why
Buy now to get the main key ideas from Judea Pearl & Dana Mackenzie's The Book of Why After decades of scientists denying causality as a real science because it could not be articulated mathematically, computer scientist Judea Pearl and his students initiated the Causal Revolution, a scientific breakthrough that embraces the human innate cognitive gift of understanding cause and effect and applies it to medical and social sciences. In The Book of Why (2020), Pearl and co-writer Dana Mackenzie browse through the history of statistics, probability, and paradoxes to showcase how human perception is steeped in causality and how emulating this retrospective thinking is the key to unlocking human-level decision-making for artificial intelligence. And it all starts with asking “Why?”
Coexistence and Other Fighting Words
The "essential" (Bari Weiss) book on Jewish identity and zionophobia, "which should be required reading" (Bernard-Henri Lévy). Catalyzed by the kidnapping and murder of his son, Wall Street Journal reporter Daniel Pearl, world-renowned computer scientist and philosopher Dr. Judea Pearl has been a relentless advocate for reason and understanding in writings and talks spanning the first quarter of the twenty-first century. Best known for his groundbreaking work on artificial intelligence, Dr Pearl turned his power of analysis to an anatomy of the hate that took his son's life, the Arab-Israeli conflict, the story of Israel, antisemitism, and other related subjects. In Coexistence and Other Fighting Words, Dr. Pearl collects the best of his work, offering an indispensable guide to some of the most pressing issues of our time.
Principles of Machine Learning
Conducting an in-depth analysis of machine learning, this book proposes three perspectives for studying machine learning: the learning frameworks, learning paradigms, and learning tasks. With this categorization, the learning frameworks reside within the theoretical perspective, the learning paradigms pertain to the methodological perspective, and the learning tasks are situated within the problematic perspective. Throughout the book, a systematic explication of machine learning principles from these three perspectives is provided, interspersed with some examples. The book is structured into four parts, encompassing a total of fifteen chapters. The inaugural part, titled “Perspectives,” ...
Probabilistic and Causal Inference
Professor Judea Pearl won the 2011 Turing Award “for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning.” This book contains the original articles that led to the award, as well as other seminal works, divided into four parts: heuristic search, probabilistic reasoning, causality, first period (1988–2001), and causality, recent period (2002–2020). Each of these parts starts with an introduction written by Judea Pearl. The volume also contains original, contributed articles by leading researchers that analyze, extend, or assess the influence of Pearl’s work in different fields: from AI, Machine Learning, and Statistics to Cognitive Science, Philosophy, and the Social Sciences. The first part of the volume includes a biography, a transcript of his Turing Award Lecture, two interviews, and a selected bibliography annotated by him.
Uncertainty in Artificial Intelligence
Uncertainty Proceedings 1994
Architects of Intelligence
Financial Times Best Books of the Year 2018 TechRepublic Top Books Every Techie Should Read Book Description How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances? Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community. Martin has wide-ranging conversations with twenty-three of the world's foremost ...
Demystifying Artificial Intelligence
This book is intended for business professionals that want to understand the fundamental concepts of Artificial Intelligence, their applications and limitations. Built as a collaborative effort between academia and the industry, this book bridges the gap between theory and business application, demystifying AI through fundamental concepts and industry examples. The reader will find here an overview of the different AI techniques to search, plan, reason, learn, adapt, understand and interact. The book covers the two traditional paradigms in AI: the statistical and data-driven AI systems, which learn and perform by ingesting millions of data points into machine learning algorithms, and the consciously modelled AI systems, known as symbolic AI systems, which use explicit symbols to represent the world and make conclusions. Rather than opposing those two paradigms, the book will also show how those different fields can complement each other. All royalties go to a charity. “Demystifying AI reveals its true power: not as a mysterious force, but as a tool for human progress, accessible to all who seek to understand it.” Dr. Barak Chizi, Chief Data & Analytics Officer, KBC Group
