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Causal Inference
- MIT Press Essential Knowledge Series
- Narrado por: Chris Monteiro
- Duración: 4 h y 25 m
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Causal Inference
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Resumen del Editor
A nontechnical guide to the basic ideas of modern causal inference, with illustrations from health, the economy, and public policy.
Which of two antiviral drugs does the most to save people infected with Ebola virus? Does a daily glass of wine prolong or shorten life? Does winning the lottery make you more or less likely to go bankrupt? How do you identify genes that cause disease? Do unions raise wages? Do some antibiotics have lethal side effects? Does the Earned Income Tax Credit help people enter the workforce?
Causal Inference provides a brief and nontechnical introduction to randomized experiments, propensity scores, natural experiments, instrumental variables, sensitivity analysis, and quasi-experimental devices. Ideas are illustrated with examples from medicine, epidemiology, economics and business, the social sciences, and public policy.
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It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.
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3 out of 5 stars
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performance is borderline unlistenable
- De jlouviere en 01-14-19
De: John D. Kelleher, y otros
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Deep Learning
- MIT Press Essential Knowledge Series
- De: John D. Kelleher
- Narrado por: Joel Richards
- Duración: 5 h y 49 m
- Versión completa
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General4 out of 5 stars 18
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Narración:4 out of 5 stars 15
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Historia4.5 out of 5 stars 15
In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.
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1 out of 5 stars
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Yikes
- De Elliot Blanford en 10-27-19
De: John D. Kelleher
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Metadata
- The MIT Press Essential Knowledge Series
- De: Jeffrey Pomerantz
- Narrado por: Steven Menasche
- Duración: 5 h y 8 m
- Versión completa
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General4 out of 5 stars 21
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Narración:4.5 out of 5 stars 19
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Historia4 out of 5 stars 17
When "metadata" became breaking news, appearing in stories about surveillance by the National Security Agency, many members of the public encountered this once-obscure term from information science for the first time. Should people be reassured that the NSA was "only" collecting metadata about phone calls - information about the caller, the recipient, the time, the duration, the location - and not recordings of the conversations themselves? Or does phone call metadata reveal more than it seems?
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5 out of 5 stars
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This Rocks!
- De Phil F. en 07-31-20
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The Art of Statistics
- How to Learn from Data
- De: David Spiegelhalter
- Narrado por: Jonathan Davis
- Duración: 9 h y 1 m
- Versión completa
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General4.5 out of 5 stars 282
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Narración:4.5 out of 5 stars 227
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Historia4.5 out of 5 stars 228
Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence - and even more so if we hope to participate in the future, rather than being simple bystanders.
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4 out of 5 stars
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very good statistics overview
- De Tom en 11-29-19
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Escape from Model Land
- How Mathematical Models Can Lead Us Astray and What We Can Do About It
- De: Erica Thompson
- Narrado por: Kirsty Dillon
- Duración: 9 h y 38 m
- Versión completa
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General4 out of 5 stars 21
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Narración:4 out of 5 stars 18
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Historia4 out of 5 stars 18
Whether we are worried about the spread of COVID-19 or making a corporate budget, we depend on mathematical models to help us understand the world around us every day. But models aren’t a mirror of reality. In fact, they are fantasies, where everything works out perfectly, every time. And relying on them too heavily can hurt us. In Escape from Model Land, statistician Erica Thompson illuminates the hidden dangers of models.
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5 out of 5 stars
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a lot of worth while substance in this book
- De Amazon Customer en 02-17-23
De: Erica Thompson
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The Book of Why
- The New Science of Cause and Effect
- De: Judea Pearl, Dana Mackenzie
- Narrado por: Mel Foster
- Duración: 15 h y 14 m
- Versión completa
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General4.5 out of 5 stars 829
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Narración:4.5 out of 5 stars 687
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Historia4.5 out of 5 stars 685
"Correlation does not imply causation". This mantra has been invoked by scientists for decades and has led to a virtual prohibition on causal talk. But today, that taboo is dead. The causal revolution, sparked by Judea Pearl and his colleagues, has cut through a century of confusion and placed causality - the study of cause and effect - on a firm scientific basis.
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5 out of 5 stars
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Great book! Not a great audiobook.
- De rrwright en 05-30-18
De: Judea Pearl, y otros
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Euclid's Window
- The Story of Geometry from Parallel Lines to Hyperspace
- De: Leonard Mlodinow
- Narrado por: Robert Blumenfeld
- Duración: 8 h y 13 m
- Versión completa
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General4 out of 5 stars 592
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Narración:4.5 out of 5 stars 419
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Historia4.5 out of 5 stars 421
Through Euclid's Window Leonard Mlodinow brilliantly and delightfully leads us on a journey through five revolutions in geometry, from the Greek concept of parallel lines to the latest notions of hyperspace. Here is an altogether new, refreshing, alternative history of math revealing how simple questions anyone might ask about space -- in the living room or in some other galaxy -- have been the hidden engine of the highest achievements in science and technology.
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5 out of 5 stars
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Wow!
- De Eric en 08-13-10
De: Leonard Mlodinow
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Standard Deviations
- Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics
- De: Gary Smith
- Narrado por: Tim Andres Pabon
- Duración: 9 h y 20 m
- Versión completa
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General4.5 out of 5 stars 357
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Narración:4.5 out of 5 stars 301
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Historia4.5 out of 5 stars 300
As Nobel Prize-winning economist Ronald Coase once cynically observed, "If you torture data long enough, it will confess." Lying with statistics is a time-honored con. In Standard Deviations, economics professor Gary Smith walks us through the various tricks and traps that people use to back up their own crackpot theories. Sometimes, the unscrupulous deliberately try to mislead us. Other times, the well-intentioned are blissfully unaware of the mischief they are committing.
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5 out of 5 stars
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Now, I can't talk to people.....
- De Andrew Dunbar en 09-28-21
De: Gary Smith
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Naked Statistics
- Stripping the Dread from the Data
- De: Charles Wheelan
- Narrado por: Jonathan Davis
- Duración: 10 h y 48 m
- Versión completa
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General4.5 out of 5 stars 3,452
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Narración:4.5 out of 5 stars 2,920
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Historia4.5 out of 5 stars 2,905
From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.
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3 out of 5 stars
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Starts well then becomes non-Audible
- De Michael en 09-07-13
De: Charles Wheelan
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Everything Is Predictable
- How Bayesian Statistics Explain Our World
- De: Tom Chivers
- Narrado por: Tom Chivers
- Duración: 8 h y 7 m
- Versión completa
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General4.5 out of 5 stars 16
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Narración:4.5 out of 5 stars 15
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Historia4.5 out of 5 stars 15
At its simplest, Bayes’s theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in Everything Is Predictable, Tom Chivers lays out how it affects every aspect of our lives. He explains why highly accurate screening tests can lead to false positives and how a failure to account for it in court has put innocent people in jail. A cornerstone of rational thought, many argue that Bayes’s theorem is a description of almost everything. But who was the man who lent his name to this theorem?
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1 out of 5 stars
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I was looking forward to this. What a disappointment.
- De Alessandro Fadini en 06-28-24
De: Tom Chivers
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The Model Thinker
- What You Need to Know to Make Data Work for You
- De: Scott E. Page
- Narrado por: Jamie Renell
- Duración: 15 h y 45 m
- Versión completa
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General4.5 out of 5 stars 44
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Narración:4.5 out of 5 stars 36
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Historia4.5 out of 5 stars 36
Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja.
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1 out of 5 stars
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It does not work on Audible
- De Hamilton Carvalho en 05-14-21
De: Scott E. Page
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Thinking in Algorithms
- How to Combine Computer Analysis and Human Creativity for Better Problem-Solving and Decision-Making: Strategic Thinking Skills, Book 2
- De: Albert Rutherford
- Narrado por: Russell Newton
- Duración: 2 h y 12 m
- Versión completa
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General4 out of 5 stars 6
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Narración:4 out of 5 stars 5
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Historia4 out of 5 stars 5
Think creatively like a human. Analyze and solve problems efficiently like a computer. Our everyday lives are filled with inefficient and ineffective decisions and solutions. Being overwhelmed by the magnitude of our problems makes it hard to think clearly. We procrastinate and overthink. Our thoughts are tainted with biases. If only there was a way to simplify our decision-making and problem-solving process and get satisfying, consistent results! The good news is, there is! Apply computer algorithms to your everyday problems.
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5 out of 5 stars
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Useful techniques to problem solve.
- De James V Wilson en 01-05-23
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Cyborg
- The MIT Press Essential Knowledge Series
- De: Laura Forlano, Danya Glabau
- Narrado por: Teri Schnaubelt
- Duración: 4 h y 9 m
- Versión completa
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General5 out of 5 stars 1
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Narración:5 out of 5 stars 1
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Historia5 out of 5 stars 1
This introduction to cyborg theory provides a critical vantage point for analyzing the claims around emerging technologies like automation, robots, and AI. Cyborg analyzes and reframes popular and scholarly conversations about cyborgs from the perspective of feminist cyborg theory.
De: Laura Forlano, y otros
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Machine Learning: The New AI
- The MIT Press Essential Knowledge Series
- De: Ethem Alpaydi
- Narrado por: Steven Menasche
- Duración: 4 h y 24 m
- Versión completa
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General4 out of 5 stars 290
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Narración:4 out of 5 stars 239
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Historia4 out of 5 stars 238
In this audiobook, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general listener, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context.
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1 out of 5 stars
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Narrator not suited to the material
- De pandrenyc en 12-01-16
De: Ethem Alpaydi
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An Introduction to Information Theory
- Symbols, Signals and Noise
- De: John R. Pierce
- Narrado por: Kyle Tait
- Duración: 10 h y 12 m
- Versión completa
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General4 out of 5 stars 53
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Narración:4.5 out of 5 stars 45
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Historia4.5 out of 5 stars 45
Behind the familiar surfaces of the telephone, radio, and television lies a sophisticated and intriguing body of knowledge known as information theory. This is the theory that has permitted the rapid development of all sorts of communication, from color television to the clear transmission of photographs from the vicinity of Jupiter. Even more revolutionary progress is expected in the future.
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3 out of 5 stars
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Not bad, but...
- De Jane Doe en 06-26-20
De: John R. Pierce
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Everything Data Analytics A Beginner's Guide to Data Literacy
- Understanding the Processes That Turn Data Into Insights
- De: Elizabeth Clarke
- Narrado por: Brennan Koenigsreuter
- Duración: 3 h y 22 m
- Versión completa
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General4.5 out of 5 stars 77
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Narración:4.5 out of 5 stars 74
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Historia4.5 out of 5 stars 74
With the world going remote, and data science following along, you can start and pursue a career in data right here, right now. How do I start? What do I need to know? What is data analytics? I'm sure one, if not all, of these questions have run through your mind. Well, the answer is data literacy: the ability to read, understand, and communicate data into information. Building a solid foundation of practical knowledge is the first step to being successful in data. From there, you can finally decide what direction you should go in and start gaining the required knowledge.
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5 out of 5 stars
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Great material for starters
- De Amazon Customer en 08-01-22
De: Elizabeth Clarke
Lo que los oyentes dicen sobre Causal Inference
Calificaciones medias de los clientesReseñas - Selecciona las pestañas a continuación para cambiar el origen de las reseñas.
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Total3 out of 5 stars
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Ejecución1 out of 5 stars
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Historia3 out of 5 stars
- Anonymous User
- 08-01-24
Not appropriate for audible and the reader don’t know how to read math
The math is read poorly. I keep hearing capital T, lowercase r. Very hard to understand.
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