Download or read book Brains Machines and Mathematics written by Michael A. Arbib and published by New York : McGraw-Hill. This book was released on 1964 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Download or read book Math for Machine Learning written by Richard Han and published by . This book was released on 2018-07-12 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains the math behind machine learning using simple but concrete examples. This book will get you started in machine learning in a smooth and natural way, preparing you for more advanced topics and dispelling the belief that machine learning is complicated, difficult, and intimidating.
Download or read book Introduction to Artificial Intelligence written by Philip C. Jackson and published by Courier Dover Publications. This book was released on 2019-08-14 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can computers think? Can they use reason to develop their own concepts, solve complex problems, understand our languages? This updated edition of a comprehensive survey includes extensive new text on "Artificial Intelligence in the 21st Century," introducing deep neural networks, conceptual graphs, languages of thought, mental models, metacognition, economic prospects, and research toward human-level AI. Ideal for both lay readers and students of computer science, the original text features abundant illustrations, diagrams, and photographs as well as challenging exercises. Lucid, easy-to-read discussions examine problem-solving methods and representations, game playing, automated understanding of natural languages, heuristic search theory, robot systems, heuristic scene analysis, predicate-calculus theorem proving, automatic programming, and many other topics.
Download or read book Weapons of Math Destruction written by Cathy O'Neil and published by Crown Publishing Group (NY). This book was released on 2016 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A former Wall Street quantitative analyst sounds an alarm on mathematical modeling, a pervasive new force in society that threatens to undermine democracy and widen inequality,"--NoveList.
Download or read book A Thousand Brains written by Jeff Hawkins and published by Basic Books. This book was released on 2021-03-02 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: A bestselling author, neuroscientist, and computer engineer unveils a theory of intelligence that will revolutionize our understanding of the brain and the future of AI. For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses maplike structures to build a model of the world—not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought. A Thousand Brains heralds a revolution in the understanding of intelligence. It is a big-think book, in every sense of the word. One of the Financial Times' Best Books of 2021 One of Bill Gates' Five Favorite Books of 2021
Download or read book Statistical Learning with Math and Python written by Joe Suzuki and published by Springer Nature. This book was released on 2021-08-03 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building Python programs. As the preliminary part, Chapter 1 provides a concise introduction to linear algebra, which will help novices read further to the following main chapters. Those succeeding chapters present essential topics in statistical learning: linear regression, classification, resampling, information criteria, regularization, nonlinear regression, decision trees, support vector machines, and unsupervised learning. Each chapter mathematically formulates and solves machine learning problems and builds the programs. The body of a chapter is accompanied by proofs and programs in an appendix, with exercises at the end of the chapter. Because the book is carefully organized to provide the solutions to the exercises in each chapter, readers can solve the total of 100 exercises by simply following the contents of each chapter. This textbook is suitable for an undergraduate or graduate course consisting of about 12 lectures. Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning.
Download or read book Mathematical Intelligence written by Mubeen Junaid and published by Simon and Schuster. This book was released on 2022-11-01 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fresh exploration into the 'human nature versus technology’ argument, revealing an unexpected advantage that humans have over our future robot masters: we’re actually good at mathematics. There’s so much discussion about the threat posed by intelligent machines that it sometimes seems as though we should simply surrender to our robot overlords now. But Junaid Mubeen isn’t ready to throw in the towel just yet. As far as he is concerned, we have the creative edge over computers, because of a remarkable system of thought that humans have developed over the millennia. It’s familiar to us all, but often badly taught in schools and misrepresented in popular discourse—math. Computers are, of course, brilliant at totting up sums, pattern-seeking, and performing mindless tasks of, well, computation. For all things calculation, machines reign supreme. But Junaid identifies seven areas of intelligence where humans can retain a crucial edge. And in exploring these areas, he opens up a fascinating world where we can develop our uniquely human mathematical talents. Just a few of the fascinating subjects covered in MATHEMATICAL INTELLIGENCE include: -Humans are endowed with a natural sense of numbers that is based on approximation rather than precise calculation. Our in-built estimation skills complement the precision of computers. Interpreting the real world depends on both. -What sets humans apart from other animals is language and abstraction. We have an extraordinary ability to create powerful representations of knowledge— more diverse than the binary language of computers. -Mathematics confers the most robust, logical framework for establishing permanent truths. Reasoning shields us from the dubious claims of pure pattern-recognition systems. -All mathematical truths are derived from a starting set of assumptions, or axioms. Unlike computers, humans have the freedom to break free of convention and examine the logical consequences of our choices. Mathematics rewards our imagination with fascinating and, on occasion, applicable concepts that originate from breaking the rules. -Computers can be tasked to solve a range of problems, but which problems are worth the effort? Questioning is as vital to our repertoire of thinking skills as problem-solving itself.
Download or read book Shadows of the Mind written by Roger Penrose and published by Oxford University Press, USA. This book was released on 1994 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the author's thesis that consciousness, in its manifestation in the human quality of understanding, is doing something that mere computation cannot; and attempts to understand how such non-computational action might arise within scientifically comprehensive physical laws.
Download or read book Probability Inequalities written by Zhengyan Lin and published by Springer Science & Business Media. This book was released on 2011-05-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inequality has become an essential tool in many areas of mathematical research, for example in probability and statistics where it is frequently used in the proofs. "Probability Inequalities" covers inequalities related with events, distribution functions, characteristic functions, moments and random variables (elements) and their sum. The book shall serve as a useful tool and reference for scientists in the areas of probability and statistics, and applied mathematics. Prof. Zhengyan Lin is a fellow of the Institute of Mathematical Statistics and currently a professor at Zhejiang University, Hangzhou, China. He is the prize winner of National Natural Science Award of China in 1997. Prof. Zhidong Bai is a fellow of TWAS and the Institute of Mathematical Statistics; he is a professor at the National University of Singapore and Northeast Normal University, Changchun, China.
Download or read book Introduction to Artificial Intelligence written by Eugene Charniak and published by Addison Wesley Publishing Company. This book was released on 1985 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Math and Architectures of Deep Learning written by Krishnendu Chaudhury and published by Simon and Schuster. This book was released on 2024-03-26 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. You'll peer inside the "black box" to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications. Math and Architectures of Deep Learning sets out the foundations of DL usefully and accessibly to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You'll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You'll be free from blind reliance on pre-packaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you'll be glad you can quickly identify and fix problems.
Download or read book Data Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Download or read book Brains Machines and Mathematics written by Michael A. Arbib and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a book whose time has come-again. The first edition (published by McGraw-Hill in 1964) was written in 1962, and it celebrated a number of approaches to developing an automata theory that could provide insights into the processing of information in brainlike machines, making it accessible to readers with no more than a college freshman's knowledge of mathematics. The book introduced many readers to aspects of cybernetics-the study of computation and control in animal and machine. But by the mid-1960s, many workers abandoned the integrated study of brains and machines to pursue artificial intelligence (AI) as an end in itself-the programming of computers to exhibit some aspects of human intelligence, but with the emphasis on achieving some benchmark of performance rather than on capturing the mechanisms by which humans were themselves intelligent. Some workers tried to use concepts from AI to model human cognition using computer programs, but were so dominated by the metaphor "the mind is a computer" that many argued that the mind must share with the computers of the 1960s the property of being serial, of executing a series of operations one at a time. As the 1960s became the 1970s, this trend continued. Meanwhile, experi mental neuroscience saw an exploration of new data on the anatomy and physiology of neural circuitry, but little of this research placed these circuits in the context of overall behavior, and little was informed by theoretical con cepts beyond feedback mechanisms and feature detectors.
Download or read book Nerds on Wall Street written by David J. Leinweber and published by Wiley. This book was released on 2009-06-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intriguing look at how technology is changing financial markets, from an innovator on the frontlines of this revolution Nerds on Wall Street tells the tale of the ongoing technological transformation of the world's financial markets. The impact of technology on investing is profound, and author David Leinweber provides readers with an overview of where we were just a few short years ago, and where we are going. Being a successful investor today and tomorrow--individual or institutional--involves more than stock picking, asset allocation, or market timing: it involves technology. And Leinweber helps readers go beyond the numbers to see exactly how this technology has become more responsible for managing modern markets. In essence, the financial game has changed and will continue to change due entirely to technology. The new "players," human or otherwise, offer investors opportunities and dangers. With this intriguing and entertaining book, Leinweber shows where technology on Wall Street has been, what it has meant, and how it will impact the markets of tomorrow.
Download or read book Thinking Machines written by Luke Dormehl and published by Penguin. This book was released on 2017-03-07 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fascinating look at Artificial Intelligence, from its humble Cold War beginnings to the dazzling future that is just around the corner. When most of us think about Artificial Intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that Artificial Intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways, the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate. In Thinking Machines, technology journalist Luke Dormehl takes you through the history of AI and how it makes up the foundations of the machines that think for us today. Furthermore, Dormehl speculates on the incredible--and possibly terrifying--future that's much closer than many would imagine. This remarkable book will invite you to marvel at what now seems commonplace and to dream about a future in which the scope of humanity may need to broaden itself to include intelligent machines.
Download or read book Pattern Recognition and Machine Intelligence written by Bhabesh Deka and published by Springer Nature. This book was released on 2019-11-25 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning; Soft and Evolutionary Computing; Image Processing; Medical Image Processing; Bioinformatics and Biomedical Signal Processing; Information Retrieval; Remote Sensing; Signal and Video Processing; and Smart and Intelligent Sensors.