Here are 100 books that Pattern Recognition and Machine Learning fans have personally recommended if you like
Pattern Recognition and Machine Learning.
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My passion for generative AI first ignited in 2016 when I spoke about it at a conference, and ever since then, I can’t stop! I've created an online course, a newsletter and even wrote a book to spread knowledge on this groundbreaking technology. As an instructor, I empower others to explore the boundless potential of generative AI applications. Day in day out, I assist clients in crafting their own generative AI solutions, tailoring them to their unique needs.
I truly believe that this is the book that brought my generation of AI experts into the fold. Despite having studied AI and ML, this book took me by the hand and grounded me in the fundamentals. I love the fact that it covers everything from mathematical basics to industry-level techniques.
Written by the OGs of deep learning, it's an absolute must-read for anyone serious about the field. Highly recommend for students and engineers alike.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
“Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all…
My passion for generative AI first ignited in 2016 when I spoke about it at a conference, and ever since then, I can’t stop! I've created an online course, a newsletter and even wrote a book to spread knowledge on this groundbreaking technology. As an instructor, I empower others to explore the boundless potential of generative AI applications. Day in day out, I assist clients in crafting their own generative AI solutions, tailoring them to their unique needs.
I absolutely love Nick Bostrom's book because it dives deep into the fascinating yet daunting future of artificial intelligence, a topic that resonates with my own work. Bostrom's exploration of how superintelligent AI could emerge and the profound risks it poses is both thought-provoking and essential reading for anyone curious about technology's trajectory.
His insights on the challenges of control and alignment really struck a chord with me, as they highlight the importance of designing AI systems that prioritize human values. This book not only raises critical questions but also inspires a sense of urgency to navigate the future responsibly, making it a personal favorite and a vital resource for anyone interested in the intersection of AI and ethics.
The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains.
If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of our species then would come to depend on the actions of the machine superintelligence.
My passion for generative AI first ignited in 2016 when I spoke about it at a conference, and ever since then, I can’t stop! I've created an online course, a newsletter and even wrote a book to spread knowledge on this groundbreaking technology. As an instructor, I empower others to explore the boundless potential of generative AI applications. Day in day out, I assist clients in crafting their own generative AI solutions, tailoring them to their unique needs.
While it’s not the newest tech, I love that it covers the essential groundwork that sparked the modern AI revolution. I personally think its perfect for engineers and data scientists. It's also a great precursor to my book, giving you the strong foundation you need before diving into the next wave of AI advancements.
Generative modeling is one of the hottest topics in AI. It's now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models.
Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you'll…
My passion for generative AI first ignited in 2016 when I spoke about it at a conference, and ever since then, I can’t stop! I've created an online course, a newsletter and even wrote a book to spread knowledge on this groundbreaking technology. As an instructor, I empower others to explore the boundless potential of generative AI applications. Day in day out, I assist clients in crafting their own generative AI solutions, tailoring them to their unique needs.
I have a deep appreciation for Stuart Russell's book because it brilliantly balances theoretical foundations with practical applications in AI. This book is not just a textbook; it’s a comprehensive guide that covers everything from problem-solving and knowledge representation to machine learning and ethics.
Russell's clear explanations and engaging examples make complex concepts accessible, which resonates with my own passion for demystifying AI for readers. I recommend it to anyone interested in understanding AI's potential and challenges, as it equips you with the knowledge to navigate this rapidly evolving field responsibly and thoughtfully.
I used to think that most nonhuman animals do not have minds in any rich sense of that word. After publishing a book about some influential philosophers who articulate and defend that view, I was pushed by a very good friend to get curious about what nonhuman creatures do. That led to years of reading, reflecting, teaching college courses, and eventually admitting that I had been profoundly wrong. My change of mind culminated in the publication of a book that explores the idea that plants have minds. The books on this list helped me tremendously along the way, and my students have also learned much from them.
I think computers don’t think, and this book taught me how to think about that. I admire it in part because it showed me, a professor of philosophy, how to do scientifically informed philosophy. Unlike so many books on the history of thinking about thinking, just the first chapter of this book is clear, accurate, insightful, and exciting. Equally so is Haugeland’s explanation of what a computer is, making an intellectual adventure of theoretical computer science.
Haugeland uses this to make a compelling case for thinking that computers could genuinely reason. And then he does something that we philosophers tend to love; he launches a provocative critique of that claim, contending that computers can’t think because they don’t “give a damn.” Although it’s now three decades old, this is the book to read if you’re curious about artificial intelligence.
First Edition. Some markings on first end page. Some shelf and edge wear, small tears, to dust jacket. Pages are clean and binding is tight. Solid Book.
I’ve always been fascinated by the power of language to propel everything we think—from our values and beliefs, to political views, to what we take for absolute truth. Once I learned there’s a whole field devoted to studying language called “rhetoric”—the field in which I’m now an expert—there was no turning back. Rhetoric has been around for more than 2,000 years, and since its inception, it has taught people to step back from language and appraise it with a more critical eye to identify how it works, why it’s persuasive, and what makes people prone to believe it. By studying rhetoric, we become less easily swayed and more comfortable with disagreement.
I love Ted Chiang’s short stories. Chiang’s background is in computer science, and he’s drawn to questions concerning the relationship between language, technology, cognition, and the physical universe.
His stories are fascinating thought experiments: They depict how a change in the medium or format of language transforms meaning and opens new possibilities for what language can be and do, what humans can think and know, and what it means to be a thinking, speaking human against the backdrop of a vast, infinitely complex universe. His stories are often backed by years of detailed research.
When I read Chiang, I find myself entangled in a strong emotional bond with his characters even as I ruminate on larger questions about what it means to be a language-using human.
'Lean, relentless, and incandescent.' Colson Whitehead, Pulitzer Prize winning author of The Underground Railroad and The Nickel Boys
This much-anticipated second collection of stories is signature Ted Chiang, full of revelatory ideas and deeply sympathetic characters. In 'The Merchant and the Alchemist's Gate,' a portal through time forces a fabric seller in ancient Baghdad to grapple with past mistakes and the temptation of second chances. In the epistolary 'Exhalation,' an alien scientist makes a shocking discovery with ramifications not just for his own people, but for all of reality. And in 'The Lifecycle of Software Objects,' a woman cares for…
I have been dreaming about Artificial Intelligence (AI) since a young age. I am currently Professor of AI at UNSW, Sydney. I was named by the Australian newspaper as one of the ”rock stars” of Australia’s digital revolution. Although this is highly improbable, I have spoken at the UN, and to heads of state, parliamentary bodies, company boards, and many others about AI and how it is impacting our lives. I've written three books about AI for a general audience that have been translated into a dozen different languages.
This is an entertaining and lighter read than my other recommendations about AI. It is specifically about chatbots trying to pass the Turing Test, and ultimately is a witty story of what it means to be human. For anyone who has ever mistaken an answerphone for a person, or a person for an answerphone!
A playful, profound book that is not only a testament to one man's efforts to be deemed more human than a computer, but also a rollicking exploration of what it means to be human in the first place.
“Terrific. ... Art and science meet an engaged mind and the friction produces real fire.” —The New Yorker
Each year, the AI community convenes to administer the famous (and famously controversial) Turing test, pitting sophisticated software programs against humans to determine if a computer can “think.” The machine that most often fools the judges wins the Most Human Computer Award. But there…
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Alan Turing’s 1936 paper “On Computable Numbers, with an Application to the Entscheidungsproblem” was foundational to the development of computer science. To this day, Turing machines, the theoretical computational devices imagined in Turing’s paper, are a research cornerstone as they embody the concept of “computable.” If a programming language can implement a Turing machine, then the language is deemed Turing complete and is, therefore, general-purpose enough to implement any algorithm.
Turing’s paper is readable, but Petzold’s book breaks it down in minute detail to explain the nomenclature and meaning behind Turing’s words. I believe all computer science students should study this paper, and you’ll be hard-pressed to find a more thorough review than the one presented in this book.
Programming Legend Charles Petzold unlocks the secrets of the extraordinary and prescient 1936 paper by Alan M. Turing
Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be computable, creating the field of computability theory in the process, a foundation of present-day computer programming.
The book expands Turing's original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing's statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math geeks,…
Coming from two very different backgrounds gives Dean and I a unique ‘view’ of a topic that we are both hugely passionate about: artificial intelligence. Our work together has gifted us a broader perspective in terms of understanding the development of and the philosophy beneath what is coined as artificial intelligence today and where we truly stand in terms of its potential for good – and evil. Our book list is intended to provide a great starting point from where you can jump into this incredibly absorbing topic and draw your own conclusions about where the future might take us.
What sets this book apart for us is its focus on rethinking the very foundations of AI. The author, Russell, thoughtfully examines the concept of intelligence itself, comparing humans and machines and outlining the necessary milestones for reaching superhuman AI.
He also doesn't shy away from the current dangers of AI misuse, providing some really great examples.
We found the book very hard to put down, and it raised so many ‘What if?” questions for us!
A leading artificial intelligence researcher lays out a new approach to AI that will enable us to coexist successfully with increasingly intelligent machines
In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable.
In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines.…
We’re a nonprofit that aims to help people have a positive social impact with their careers. Since you have, on average, 80,000 hours in your career, what you decide to do with that time might be your biggest opportunity to make a difference. Over the past ten years, we’ve conducted careful research into high-impact careers, and have helped thousands of people plan a career that has a high positive impact.
One example of an especially pressing threat facing humanity is the rapid development of artificial intelligence. If we want this new technology to go well, it needs to be ‘aligned’ – that is, it should have or act on the same values as us.
In this book, Brian sets out why aligning artificial intelligence is an extremely tricky issue and one which deserves more attention from talented and dedicated people.
Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us-and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem.
Systems cull resumes until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole-and appear to assess Black…
