Here are 100 books that The Shortcut fans have personally recommended if you like
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I started my career in neuroscience. I wanted to understand brains. That is still proving difficult, and somewhere along the way, I realized my real motivation was to build things, and I wound up working in AI. I love the elegance of mathematical models of the world. Even the simplest machine learning model has complex implications, and exploring them is a joy.
The best parts of this book really represent a gold standard in pedagogical clarity.
Although it’s now twenty years old, there is still much to learn from this rather unconventional book that covers the boundary between machine learning, information theory, and Bayesian methods. There are also odd tangents and curiosities, some of which work better than others but are never dull.
Just writing this review makes me want to go back to it and squeeze more out of it.
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo…
I started my career in neuroscience. I wanted to understand brains. That is still proving difficult, and somewhere along the way, I realized my real motivation was to build things, and I wound up working in AI. I love the elegance of mathematical models of the world. Even the simplest machine learning model has complex implications, and exploring them is a joy.
My knees tremble and my heart quakes when I think of how much work must have gone into these two companion volumes. Collectively, they are more than four times the length of my book, covering the whole of machine learning.
It is an essential encyclopedic resource that should be on the desk of anyone serious about machine learning.
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.
This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation.
I started my career in neuroscience. I wanted to understand brains. That is still proving difficult, and somewhere along the way, I realized my real motivation was to build things, and I wound up working in AI. I love the elegance of mathematical models of the world. Even the simplest machine learning model has complex implications, and exploring them is a joy.
This is the practical book that best accompanies my book (which is more about the underlying ideas.)
If you want a book that will show you how deep learning systems are built in practice, then this is the best place to start. It’s full of code snippets that translate between theory and building real systems.
Deep learning has revolutionized pattern recognition, introducing tools that power a wide range of technologies in such diverse fields as computer vision, natural language processing, and automatic speech recognition. Applying deep learning requires you to simultaneously understand how to cast a problem, the basic mathematics of modeling, the algorithms for fitting your models to data, and the engineering techniques to implement it all. This book is a comprehensive resource that makes deep learning approachable, while still providing sufficient technical depth to enable engineers, scientists, and students to use deep learning in their own work. No previous background in machine learning…
I started my career in neuroscience. I wanted to understand brains. That is still proving difficult, and somewhere along the way, I realized my real motivation was to build things, and I wound up working in AI. I love the elegance of mathematical models of the world. Even the simplest machine learning model has complex implications, and exploring them is a joy.
Of course, this is not the obvious book to recommend for reinforcement learning, but if you are a beginner, then it’s a quick and easy place to start. It’s compact and gets straight into the main algorithms.
It has a good balance between theory and code and will get you up and running quickly.
The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice
Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games-such as Go, Atari games, and DotA 2-to robotics.
Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM…
I am a retired university professor. My research, in which I am still actively engaged, deals with decision-making under deep uncertainty: how to make a decision, or design a project, or plan an operation when major relevant factors are unknown or highly uncertain. I developed a decision theory called info-gap theory that grapples with this challenge, and is applied around the world in many fields, including engineering design, economics, medicine, national security, biological conservation, and more.
The world is complicated and confusing, but Harari organizes this complexity into 21 issues covering such diverse topics as liberty, community, war, ignorance, and meaning.
The book is a collection of self-standing essays that can be read independently. The prevailing message is that we can understand the world in which we live, though, at the same time, we cannot always make reliable decisions today or confidently predict the future because we fundamentally don't know what's going on.
Finally, the book offers a warning: modern technology, coupled with artificial intelligence, may challenge human freedom if we lose control of the powerful and evolving forces of hi-tech and AI.
In twenty-one bite-sized lessons, Yuval Noah Harari explores what it means to be human in an age of bewilderment.
How can we protect ourselves from nuclear war, ecological cataclysms and technological disruptions? What can we do about the epidemic of fake news or the threat of terrorism? What should we teach our children?
The world-renowned historian and intellectual Yuval Noah Harari takes us on a thrilling journey through today's most urgent issues. The golden thread running through his exhilarating new book is the challenge of maintaining our collective and individual focus in the face of constant…
I became fascinated by the highest achievements of human intelligence while a graduate student in philosophy working on the discovery and justification of scientific theories. Shortly after I got my PhD, I started working with cognitive psychologists who gave me an appreciation for empirical studies of intelligent thinking. Psychology led me to computational modeling of intelligence and I learned to build my own models. Much later a graduate student got me interested in questions about intelligence in non-human animals. After teaching a course on intelligence in machines, humans, and other animals, I decided to write a book that provides a systematic comparison: Bots and Beasts.
This book provides a good introduction to the current state of machine intelligence through interviews with many leading practitioners including Geoffrey Hinton, Yann LeCun, Stuart Russell, and Demis Hassabis (DeepMind). You will get a sense of both of AI’s recent accomplishments and how far it falls short of full human intelligence.
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…
I was stimulated by Norbert Wiener’s “Cybernetics” to study circuits in the brain that control behavior. For my graduate studies, I chose the olfactory bulb for its experimental advantages, which led to constructing the first computer models of brain neurons and microcircuits. Then I got interested in how the smell patterns are activated when we eat food, which led to a new field called Neurogastronomy, which is the neuroscience of the circuits that create the perception of food flavor. Finally, because all animals use their brains to find and eat food, the olfactory system has provided new insights into the evolution of the mammalian brain and the basic organization of the cerebral cortex.
The other books in this series are mostly about the real brain. But artificial intelligence promises us a new enhanced brain. What does the future hold? Terrence Sejnowski is a neuroscientist who was one of the first to realize the potential of AI. Since he has been there from the start, in this book he gives the reader an exciting inside story on the people and the advances that are reshaping our lives.
Early attempts at AI were limited, but once computational power took off big computers running multilayer neural nets began proving that they could defeat humans at the most demanding games, enhance human capabilities such as pattern recognition, text recognition, language translation, and driverless vehicles, and work to obtain rewards, just like a human. While these advances are dramatic, it is well to remember that the networks are built not from representations of real neurons, but rather from…
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
I’ve been a geeky kid all my life. (I don’t think I’ve quite grown up yet.) Born in the 1970s, my childhood was a wonderful playground of building robots and software. I was awarded one of the early degrees in AI, and a PhD in genetic algorithms. I’ve since spent 25 years exploring how to make computers think, build, invent, compose… and I’ve also spent 20 years writing popular science books. I’m lucky enough to be a Professor in one of the world’s best universities for Computer Science and Machine Learning: UCL, and I guess I’ve written two or three hundred scientific papers over the years. I still think I know nothing at all about real or artificial intelligence, but then does anyone?
I’ve not met Harry, but he seems to have a logical and sensible head on his shoulders. His writing is considered and grounded, which is exactly what you need when discussing the hype that forever seems to surround AI. This book is another look at this topic and finds yet more ways to explain to readers the difference between human intelligence and our algorithmic attempts at intelligence – which are frequently pretty stupid.
Recent startling successes in machine intelligence using a technique called 'deep learning' seem to blur the line between human and machine as never before. Are computers on the cusp of becoming so intelligent that they will render humans obsolete? Harry Collins argues we are getting ahead of ourselves, caught up in images of a fantastical future dreamt up in fictional portrayals. The greater present danger is that we lose sight of the very real limitations of artificial intelligence and readily enslave ourselves to stupid computers: the 'Surrender'.
By dissecting the intricacies of language use and meaning, Collins shows how far…
I’m not ashamed to admit that my childhood fascination with the distant past was sparked by hours of leafing through The Kingfisher Illustrated History of the Worldand countless viewings of the “Indiana Jones” movies. Today, I am an Associate Professor in the Department of Humanities at Mercy College and an archaeologist specializing in the eastern Alpine region during Late Antiquity and the Early Middle Ages. The author of three books and numerous scholarly articles, my research interests include ceramic technology, social identity, and the appropriation of the medieval past by modern ideologies.
When I first read this book as a graduate student, Kathleen Davis’s ability to draw unexpected connections—between political power and temporality, feudalism and imperialism, medieval and postcolonial studies—melted my brain (in a good way). It’s not easy to do justice to her complex argument in a few sentences, but basically she shows how early modern jurists deliberately relegated certain ideas (servility, absolutism, religiosity) both to Europe’s medieval past and the present of the nonwestern world in order to justify imperial expansion, colonial domination, and even chattel slavery. A dense critique of both medieval historiography and postcolonial theory, Periodization and Sovereignty isn’t a breezy read but it’s well worth the effort.
Despite all recent challenges to stage-oriented histories, the idea of a division between a "medieval" and a "modern" period has survived, even flourished, in academia. Periodization and Sovereignty demonstrates that this survival is no innocent affair. By examining periodization together with the two controversial categories of feudalism and secularization, Kathleen Davis exposes the relationship between the constitution of "the Middle Ages" and the history of sovereignty, slavery, and colonialism.
This book's groundbreaking investigation of feudal historiography finds that the historical formation of "feudalism" mediated the theorization of sovereignty and a social contract, even as it provided a rationale for colonialism…
I'm a professor of rhetoric at the University of Houston – Downtown. In addition to my academic research, I write political and cultural commentary for a variety of right-of-center online publications. Much of my own work focuses on how individuals come to be persuaded about who they are. I argue that much of the frustration people feel when searching for their authentic identity is due to the fact that the existence of the hidden ‘true self’ is an illusion. The quest for authenticity is never complete. The good news, though, is that you can put an end to the suffering… only if you’re willing to give up the fevered pursuit of the “true self.”
While Trueman reviews some of the ideas covered by other thinkers on this list, his new book is notable because it focuses on how personal sexual identity (sexual orientation, gender, desire, etc.) came to be the most important site for the expression of individualism. His analysis underscores the threat that a radically subjectivized sexual ethic posed to longstanding social norms and cultural traditions. This one also includes a gushing foreword by best-selling author Rod Dreher of The American Conservative magazine.
Carl Trueman traces the historical roots of many hot-button issues such as transgenderism and homosexuality, offering thoughtful biblical analysis as he uncovers the profound impact of the sexual revolution on modern human identity.
