Deep Code

Accurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging. It has fundamentally changed the way modern image reconstruction is performed. This in-depth treatment of the subject commences with a practical introduction to compressive imaging, supplemented with examples and downloadable code, intended for readers without extensive background in the subject. Next, it introduces core topics in compressive imaging – including compressed sensing, wavelets and optimization – in a concise yet rigorous way, before providing a detailed treatment of the mathematics of compressive imaging. The final part is devoted to recent trends in compressive imaging: deep learning and neural networks. With an eye to the next decade of imaging research, and using both empirical and mathematical insights, it examines the potential benefits and the

Data are not only ubiquitous in society, but are increasingly complex both in size and dimensionality. Dimension reduction offers researchers and scholars the ability to make such complex, high dimensional data spaces simpler and more manageable. This Element offers readers a suite of modern unsupervised dimension reduction techniques along with hundreds of lines of R code, to efficiently represent the original high dimensional data space in a simplified, lower dimensional subspace. Launching from the earliest dimension reduction technique principal components analysis and using real social science data, I introduce and walk readers through application of the following techniques: locally linear embedding, t-distributed stochastic neighbor embedding (t-SNE), uniform manifold approximation and projection, self-organizing maps, and deep autoencoders. The result is a well-stocked toolbox of unsupervised algorithms for tackling the complexities of high dimensional data so common in modern

A unique text integrating numerics, mathematics and applications to provide a hands-on approach to using optimization techniques, this mathematically accessible textbook emphasises conceptual understanding and importance of theorems rather than elaborate proofs. It allows students to develop fundamental optimization methods before delving into MATLAB®'s optimization toolbox, and to link MATLAB's results with the results from their own code. Following a practical approach, the text demonstrates several applications, from error-free analytic examples to truss (size) optimization, and 2D and 3D shape optimization, where numerical errors are inevitable. The principle of minimum potential energy is discussed to highlight the deep relationship between engineering and optimization. MATLAB code in every chapter illustrates key concepts and the text demonstrates the coupling between MATLAB and SOLIDWORKS® for design optimization. A wide variety of optimization problems are covered including con

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an onli

Deep learning is revolutionizing how machine translation systems are built today. This book introduces the challenge of machine translation and evaluation - including historical, linguistic, and applied context -- then develops the core deep learning methods used for natural language applications. Code examples in Python give readers a hands-on blueprint for understanding and implementing their own machine translation systems. The book also provides extensive coverage of machine learning tricks, issues involved in handling various forms of data, model enhancements, and current challenges and methods for analysis and visualization. Summaries of the current research in the field make this a state-of-the-art textbook for undergraduate and graduate classes, as well as an essential reference for researchers and developers interested in other applications of neural methods in the broader field of human language processing.

Finite-state methods are the most efficient mechanisms for analysing textual and symbolic data, providing elegant solutions for an immense number of practical problems in computational linguistics and computer science. This book for graduate students and researchers gives a complete coverage of the field, starting from a conceptual introduction and building to advanced topics and applications. The central finite-state technologies are introduced with mathematical rigour, ranging from simple finite-state automata to transducers and bimachines as 'input-output' devices. Special attention is given to the rich possibilities of simplifying, transforming and combining finite-state devices. All algorithms presented are accompanied by full correctness proofs and executable source code in a new programming language, C(M), which focuses on transparency of steps and simplicity of code. Thus, by enabling readers to obtain a deep formal understanding of the subject and to put finite-state methods t

Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday de

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A CODE HIDDEN IN PLAIN SIGHT. A BLACK OPS TEAM THAT WENT TOO FAR.John Hayes is a Special Operations legend who went rogue on a deep-cover mission and betrayed his own soldiers. Disgraced and on the ru

Cell: no service. Email: down. Internet: off. TV: nothing. Radio: static. Communication: minimal. Chaos: unstoppable. Press Any Key to Start. PR hack Tristan Schultz is buried deep in the endless code

Sphinx: the Ancient Gods are Awakening. Are We Ready? When a team of westerners discovers a mysterious code hidden deep within the fabric of the Great Pyramid, they unearth a secret that has been hidd

"One of China's bestselling novels, an unusual literary thriller that takes us deep into the world of code breaking In his gripping debut novel, Mai Jia reveals the mysterious world of Unit 701, a top

Along with updating all chapters and Python code examples, the second edition of this bestseller includes new chapters on Gaussian processes, Boltzmann machines, and deep belief networks. It also revi

One of China’s bestselling novels, an unusual literary thriller that takes us deep into the world of code breakingIn his gripping debut novel, Mai Jia reveals the mysterious world of Unit 701, a top-s

Spring, 1943. The war is turning against Germany, but Hitler isn't giving up. In a secret bunker deep in occupied France, scientists are hard at work on Hitler's latest deadly weapon: code name FZG-76

Joe Celko has looked deep into the code of SQL programmers and found a consistent and troubling pattern - a frightening lack of consistency between their individual encoding schemes and those of the i

This book, first published in 2000, explores the exciting field of complexity. It features in-depth coverage of important theoretical areas, including fractals, chaos, non-linear dynamics, artificial life and self-organization. It also provides overviews of complexity in several applied areas, including parallel computation, control systems, neural systems and ecosystems. Some of the properties that best characterize complex systems, including algorithmic richness, non-linearity and abundant interactions between components are examined. In this way the book draws out themes, especially the ideas of connectivity and natural computation, that reveal deep, underlying similarities between phenomena that have formerly been treated as completely distinct. The idea of natural computation is particularly rich in fresh approaches applicable to both biology and computing. Analogies such as the DNA code as life's underlying program, or organisms as automata, are very compelling. Conversely, biolo

This book, first published in 2000, explores the exciting field of complexity. It features in-depth coverage of important theoretical areas, including fractals, chaos, non-linear dynamics, artificial life and self-organization. It also provides overviews of complexity in several applied areas, including parallel computation, control systems, neural systems and ecosystems. Some of the properties that best characterize complex systems, including algorithmic richness, non-linearity and abundant interactions between components are examined. In this way the book draws out themes, especially the ideas of connectivity and natural computation, that reveal deep, underlying similarities between phenomena that have formerly been treated as completely distinct. The idea of natural computation is particularly rich in fresh approaches applicable to both biology and computing. Analogies such as the DNA code as life's underlying program, or organisms as automata, are very compelling. Conversely, biolo

The explosion at the Prime Minister's visit to Long Harbour means the cover of the Monster Republic is blown, and they are forced deep into hiding. Lazarus Fry turns his tactics to infiltration, and i

If you want to ensure a bright future for your child thank to coding, then keep reading...Hey you, father or mother that are reading these lines, let me introduce myself. I'm Raymond Deep, expert programmer since 1999 and father of two wonderful kids.Do you know that the median annual wage for computer programmers was $86,550 in 2019? I want, like you, give a chance to my childs and, you know, coding is the skill that each one wants on the market.Children want to have fun and I was looking for, without ever being satisfied, a product that would explain step by step, without the intervention of a parent and in a funny way, how to start writing the first line of code.Searching on internet, I discovered an image-based programming language that is perfect for kids to learn the logic of programming, how a programmer has to think: SCRATCH 3.This language/tool is fantastic and, because I'm an experienced programmer, I saw the big potential and I started to study all details and features of th

The award-winning author of The Music of the Primes explores the future of creativity and how machine learning will disrupt, enrich, and transform our understanding of what it means to be human.Can a well-programmed machine do anything a human can—only better? Complex algorithms are buying our groceries, picking our partners, and driving our investments. They can navigate more data than a doctor or lawyer and act with greater precision. For many years we’ve taken solace in the notion that they can’t create. But now that algorithms can learn and adapt, does the future of creativity belong to machines too?It is hard to imagine a better guide to the bewildering world of artificial intelligence than Marcus du Sautoy, a celebrated Oxford mathematician whose work on symmetry in the ninth dimension has taken him to the vertiginous edge of mathematical understanding. In The Creativity Code he considers what machine learning means for the future of creativity. Programs like Deep Dream produce d

Deep beneath the city live five extraordinary kids: world-famous hacker Jack, gadget geek Charlie, free runner Slink, communications chief Obi, and decoy expert Wren. Orphans bonded over their shared sense of justice, the kids have formed the Urban Outlaws, a group dedicated to outsmarting criminals and handing out their stolen money through Random Acts of Kindness (R.A.K.s).But the kids find themselves in serious trouble when they're caught in an epic battle to control Proteus, a genius super-computer. Proteus can crack any code in the world-and steal top-secret documents in nanoseconds. It's down to the Urban Outlaws to use their guile, guts, and skill to destroy the computer, avert world domination . . . and stay alive.Don't miss the global launch of this debut series from Peter Jay Black-the perfect mix of explosive action, cool technology, and characters with lots of heart.

Deep beneath the city live five extraordinary kids: world-famous hacker Jack, gadget geek Charlie, free runner Slink, communications chief Obi, and decoy expert Wren. Orphans bonded over their shared sense of justice, the kids have formed the Urban Outlaws, a group dedicated to outsmarting criminals and handing out their stolen money through Random Acts of Kindness (R.A.K.s).But the kids find themselves in serious trouble when they're caught in an epic battle to control Proteus, a genius super-computer. Proteus can crack any code in the world—and steal top-secret documents in nanoseconds. It's down to the Urban Outlaws to use their guile, guts, and skill to destroy the computer, avert world domination . . . and stay alive.Don't miss the global launch of this debut series from Peter Jay Black—the perfect mix of explosive action, cool technology, and characters with lots of heart.