Tammet's ability to think abstractly, deviate from routine, and empathize, interact and communicate with others is impaired, yet he's capable of incredible feats of memorization and mental calculation. Besides being able to effortlessly multiply and divide huge sums in his head with the speed and accuracy of a computer, Tammet, the subject of the 2005 documentary Brainman, learned Icelandic in a single week and recited the number pi up to the 22,514th digit, breaking the European record. He also experiences synesthesia, an unusual neurological syndrome that enables him to experience numbers and words as "shapes, colors, textures and motions." Tammet traces his life from a frustrating, withdrawn childhood and adolescence to his adult achievements, which include teaching in Lithuania, achieving financial independence with an educational Web site and sustaining a long-term romantic relationship. As one of only about 50 people living today with synesthesia and autism, Tammet's condition is intriguing to researchers; his ability to express himself clearly and with a surprisingly engaging tone (given his symptoms) makes for an account that will intrigue others as well.

    The top-selling CS review book written by students and IMGs who recently passed 100+ high-yield minicases by chief complaint 30 complete cases simulate the exam experience Contains new Patient Encounters, including telephone interviews Perfect for group or solo study YOUR COMPLETE CS SURVIVAL GUIDE FROM THE AUTHORS OF FIRST AID FOR THE USMLE STEP 1 INSIDER ADVICE FOR STEP 2 CS SUCCESS New miniguide shows US students and IMGs how best to use this book Revised by test veterans to reflect the 2005--2006 exam experience Each complete case features standardized patient checklists and a recommended clinical approach Minicases represent the major chief complaints and diagnoses seen on the Step 2 CS Proven strategies for the patient encounter and patient note High-yield, must-know facts on patient diagnosis and workup.

    

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    This second edition is appropriate as a supplementary (companion) text for any college-level course covering digital signal processing.

    

    One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

    From his intimate knowledge of S., the mnemonist, gained from conversations and testing over a period of almost thirty years, A. R. Luria is able to reveal in rich detail not only the obvious strengths of S.’s astonishing memory but also his surprising weaknesses: his crippling inability to forget, his pattern of reacting passively to life, and his uniquely handicapped personality.

    Of particular importance is the examination of Bayesianism and the new experimentalism, as well as new chapters on the nature of scientific laws and recent trends in the realism versus anti-realism debate."Crisp, lucid and studded with telling examples… As a handy guide to recent alarums and excursions (in the philosophy of science) I find this book vigorous, gallant and useful."New Scientist

    Written by A330 Captain, Bill Palmer, this book opens to understanding the actions of the crew, how they failed to understand and control the problem, and how the airplane works and the part it played. All in easy to understand terms.Addressed are the many contributing aspects of weather, human factors, and airplane system operation and design that the crew could not recover from. How each contributed is covered in detail along with what has been done, and needs to be done in the future to prevent this from happening again.Also see the book's companion website: UnderstandingAF447.com for supplemental materials referred to in the book or to contact the author.

    The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks.The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.

    However, according to Hofstadter, the formal system that underlies all mental activity transcends the system that supports it. If life can grow out of the formal chemical substrate of the cell, if consciousness can emerge out of a formal system of firing neurons, then so too will computers attain human intelligence. Gödel, Escher, Bach is a wonderful exploration of fascinating ideas at the heart of cognitive science: meaning, reduction, recursion, and much more.

    This is incidental as it is about neither of those industries in particular. It is about the magic and wonderment of those days as seen through the eyes of a child – my eyes! It is about the days when imagination was the biggest plaything that we possessed. The days when a plastic football provided a whole summer's play. It is about the scrapes that I found myself in and the things that I observed around me, and how they made me feel. All the stories are true and I personally experienced every one of them. The names of the characters have been changed. The reason being that I have no idea of the whereabouts of many of the characters contained within my stories, so I have no way of asking them for their permission to include them in this book. Some have possibly passed away, and it would be unfair of me to mention them without their blessing. Anyone who knows me will know who they are though.

    Simmons advocates a careful approach to the subject, covering such topics as the wave equation, Gauss's hypergeometric function, the gamma function and the basic problems of the calculus of variations in an explanatory fashions - ensuring that students fully understand and appreciate the topics.

    In this virtuosic work of popular science, neuroscientist and best-selling author Dean Buonomano investigates the intricate relationship between the brain and time: What is time? Why does time seem to speed up or slow down? Is our sense that time flows an illusion? Buonomano presents his own influential theory of how the brain tells time, and he illuminates such concepts as free will, consciousness, spacetime, and relativity from the perspective of a neuroscientist. Drawing on physics, evolutionary biology, and philosophy, Your Brain Is a Time Machine reveals that the brain’s ultimate purpose may be to predict the future, and thus that your brain is a time machine.