We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning.

Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the 17th-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it.

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.

Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger - all by the time he was 30. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data.

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.

Perfect for beginners wanting to learn about Bayes Theorem through real examples! What if you could quickly and easily learn Bayesian data analysis without complex textbooks and statistics classes? Imagine being able to apply your newly learned theory to real life situations! If you are a person that learns by example, then this audiobook is perfect for you! It is a very important topic in a wide range of industries - so dive in to get a deep understanding!

Life is full of uncertainty. You don't know what lies ahead. But you can learn to control the controllable by using logic and reason. With the help of this book, you'll discover new ways to think about - and solve - problems more efficiently than ever before. Discover how strategic games model real-life behavior.

When he was six years old, Roger Penrose discovered a sundial in a clearing near his house. Through that machine made of light, shadow, and time, Roger glimpsed a “world behind the world” of transcendently beautiful geometry. It spurred him on a journey to become one of the world’s most influential mathematicians, philosophers, and physicists. Penrose would prove the limitations of general relativity, set a new agenda for theoretical physics, and astound colleagues and admirers with the elegance and beauty of his discoveries.

Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics - we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us”.

How Not To Invest shows you a few simple tools and models that will help you avoid the most common mistakes people make with their money. Learn these, and you are ahead of 98% of your peers. Make fewer errors, end up with more money. We all make mistakes. The goal with this book is to help you make fewer of them, and to have the mistakes you do make be less expensive.

Become a better decision-maker and more informed consumer using statistics stories. Stories stimulate our brains to enhance retention and understanding by evoking emotions. They provide context, helping us grasp complex concepts through real-life examples and establish a connection with the information. By transforming data into narratives, we recall and thus apply insights more effectively, enhancing our ability to make more informed decisions. Perfect for the Math-Averse. You don’t need to crunch numbers to make statistics valuable.

There’s no doubt that our world has gotten more extreme. Pandemics, climate change, superpower rivalries, cyberattacks, political radicalization—virtually, everywhere we look there is mayhem bearing down on us, putting trillions of assets at risk. And at least two factions have formed around how to respond. In Chaos Kings, Scott Patterson depicts how one faction, led by Nassim Nicholas Taleb, bestselling author of The Black Swan, believes humans can never see the big disaster coming.

In the late 1850s, a physician in New York City used a syringe and glass tube to inject half a drop of sperm into a woman's uterus, marking the first recorded instance of artificial insemination. From that day forward, doctors and scientists have turned to technology in ever more innovative ways to facilitate conception. Fertility Technology surveys this history in all its medical, practical, and ethical complexity, and offers a look at state-of-the-art fertility technology in various social and political contexts around the world.

Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia's views on crime and punishment, the psychology of slime molds, what Facebook can and can't figure out about you, and the existence of God.

How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in AI strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network? As Peter Robin Hiesinger argues, "the information problem" underlies both fields.

Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the 17th-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it.

We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning.

Become a better decision-maker and more informed consumer using statistics stories. Stories stimulate our brains to enhance retention and understanding by evoking emotions. They provide context, helping us grasp complex concepts through real-life examples and establish a connection with the information. By transforming data into narratives, we recall and thus apply insights more effectively, enhancing our ability to make more informed decisions. Perfect for the Math-Averse. You don’t need to crunch numbers to make statistics valuable.

Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia's views on crime and punishment, the psychology of slime molds, what Facebook can and can't figure out about you, and the existence of God.

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.

Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. Sharon Bertsch McGrayne here explores this controversial theorem and the human obsessions surrounding it.

Exploring and explaining a litany of glitches, near misses, and mathematical mishaps involving the internet, big data, elections, street signs, lotteries, the Roman Empire, and an Olympic team, Matt Parker uncovers the bizarre ways math trips us up, and what this reveals about its essential place in our world. Getting it wrong has never been more fun.

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.

This book reveals how statistics and probability are fundamental to our everyday lives—from advertisements to public opinion polls, weather forecasts to government policies, scientific research to stock market information. Haim Shapira then presents a myriad of anecdotes, riddles, case studies and practical exercises in his trademark witty voice to guide the listner through the importance of statistics and probability in everyday life.

This is an audiobook about AI and AI risk. But it's also more importantly about a community of people who are trying to think rationally about intelligence, and the places that these thoughts are taking them, and what insight they can and can't give us about the future of the human race over the next few years. It explains why these people are worried, why they might be right and why they might be wrong.

In the bestselling The Signal and the Noise, Nate Silver showed how forecasting would define the age of Big Data. Now, in this timely and riveting new book, Silver investigates "The River," or those whose mastery of risk allows them to shape—and dominate—so much of modern life. These professional risk takers—poker players and hedge fund managers, crypto true-believers and blue-chip art collectors—can teach us much about navigating the uncertainty of the 21st century.

Bertrand Russell wrote that mathematics can exalt "as surely as poetry". This is especially true of one equation: ei(pi) + 1 = 0, the brainchild of Leonhard Euler, the Mozart of mathematics. More than two centuries after Euler's death, it is still regarded as a conceptual diamond of unsurpassed beauty. Called Euler's identity, or God's equation, it includes just five numbers but represents an astonishing revelation of hidden connections.

AI expert Yorick Wilks takes a journey through the history of artificial intelligence up to the present day, examining its origins, controversies, and achievements, as well as looking into just how it works. He also considers the future, assessing whether these technologies could menace our way of life and how we are all likely to benefit from AI applications in the years to come.

Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics - we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us”.

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.