Download Free Deep Design Book in PDF and EPUB Free Download. You can read online Deep Design and write the review.

In Deep Design, David Wann explores a new way of thinking about design, one that asks "What is our ultimate goal?" before the first step has even been taken. Designs that begin with such a question -- whether in products, buildings, technologies, or communities -- are sensitive to living systems, and can potentially accomplish their mission without the seemingly unavoidable side effects of pollution, erosion, congestion, and stress. Such "deep designs" meet the key criteria of renewability, recyclability, and nontoxicity. Often based on natural systems, they are easy to understand and implement, and provide more elegant approaches to getting the services and functions we need. Wann presents information gleaned from interviews with more than fifty innovative designers in a wide variety of fields, and describes numerous case studies that explain the concept and practice of deep design.
Does the universe embody beautiful ideas? Artists as well as scientists throughout human history have pondered this “beautiful question.” With Nobel laureate Frank Wilczek as your guide, embark on a voyage of related discoveries, from Plato and Pythagoras up to the present. Wilczek’s groundbreaking work in quantum physics was inspired by his intuition to look for a deeper order of beauty in nature. This is the deep logic of the universe—and it is no accident that it is also at the heart of what we find aesthetically pleasing and inspiring. Wilczek is hardly alone among great scientists in charting his course using beauty as his compass. As he reveals in A Beautiful Question, this has been the heart of scientific pursuit from Pythagoras and the ancient belief in the music of the spheres to Galileo, Newton, Maxwell, Einstein, and into the deep waters of twentieth-century physics. Wilczek brings us right to the edge of knowledge today, where the core insights of even the craziest quantum ideas apply principles we all understand. The equations for atoms and light are almost the same ones that govern musical instruments and sound; the subatomic particles that are responsible for most of our mass are determined by simple geometric symmetries. Gorgeously illustrated, A Beautiful Question is a mind-shifting book that braids the age-old quest for beauty and the age-old quest for truth into a thrilling synthesis. It is a dazzling and important work from one of our best thinkers, whose humor and infectious sense of wonder animate every page. Yes: The world is a work of art, and its deepest truths are ones we already feel, as if they were somehow written in our souls.
One-of-a-kind coverage on the fundamentals of foundation analysis and design Analysis and Design of Shallow and Deep Foundations is a significant new resource to the engineering principles used in the analysis and design of both shallow and deep, load-bearing foundations for a variety of building and structural types. Its unique presentation focuses on new developments in computer-aided analysis and soil-structure interaction, including foundations as deformable bodies. Written by the world's leading foundation engineers, Analysis and Design of Shallow and Deep Foundations covers everything from soil investigations and loading analysis to major types of foundations and construction methods. It also features: * Coverage on computer-assisted analytical methods, balanced with standard methods such as site visits and the role of engineering geology * Methods for computing the capacity and settlement of both shallow and deep foundations * Field-testing methods and sample case studies, including projects where foundations have failed, supported with analyses of the failure * CD-ROM containing demonstration versions of analytical geotechnical software from Ensoft, Inc. tailored for use by students in the classroom
By Libby Lumpkin.
Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will learn: Internal functioning of modern convolutional neural networks Procedural reuse design pattern for CNN architectures Models for mobile and IoT devices Assembling large-scale model deployments Optimizing hyperparameter tuning Migrating a model to a production environment The big challenge of deep learning lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Patterns and Practices is here to help. This unique guide lays out the latest deep learning insights from author Andrew Ferlitsch’s work with Google Cloud AI. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Each valuable technique is presented in a way that's easy to understand and filled with accessible diagrams and code samples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Discover best practices, design patterns, and reproducible architectures that will guide your deep learning projects from the lab into production. This awesome book collects and illuminates the most relevant insights from a decade of real world deep learning experience. You’ll build your skills and confidence with each interesting example. About the book Deep Learning Patterns and Practices is a deep dive into building successful deep learning applications. You’ll save hours of trial-and-error by applying proven patterns and practices to your own projects. Tested code samples, real-world examples, and a brilliant narrative style make even complex concepts simple and engaging. Along the way, you’ll get tips for deploying, testing, and maintaining your projects. What's inside Modern convolutional neural networks Design pattern for CNN architectures Models for mobile and IoT devices Large-scale model deployments Examples for computer vision About the reader For machine learning engineers familiar with Python and deep learning. About the author Andrew Ferlitsch is an expert on computer vision, deep learning, and operationalizing ML in production at Google Cloud AI Developer Relations. Table of Contents PART 1 DEEP LEARNING FUNDAMENTALS 1 Designing modern machine learning 2 Deep neural networks 3 Convolutional and residual neural networks 4 Training fundamentals PART 2 BASIC DESIGN PATTERN 5 Procedural design pattern 6 Wide convolutional neural networks 7 Alternative connectivity patterns 8 Mobile convolutional neural networks 9 Autoencoders PART 3 WORKING WITH PIPELINES 10 Hyperparameter tuning 11 Transfer learning 12 Data distributions 13 Data pipeline 14 Training and deployment pipeline
Game Design Deep Dive: Roguelikes examines the history and rise of the often-confusing roguelike genre. Despite being more than 30 years old, the roguelike genre remains a mystery to a lot of consumers and developers. Procedural generation, or having the game generate content, has been a cornerstone and point of complexity since its inception. The 2010s saw an explosion of new designs and examples, along with a debate about what a roguelike is. The genre found its way back to mainstream audiences with the award-winning Demon’s Souls and Dark Souls. Since then, roguelikes have revolutionized the way we see and design games. Author and game design critic Joshua Bycer explains the differences between the various roguelike designs and give a detailed blueprint showing what makes the best ones work. The first of its kind talking about the roguelike genre Examines the design and methodology of roguelike games and the different variations A high-level discussion and breakdown of procedural and random content generation Joshua Bycer is a game design critic with more than seven years of experience critically analyzing game design and the industry itself. In that time, through Game-Wisdom, he has interviewed hundreds of game developers and members of the industry about what it means to design video games. He is also a public speaker and presenter at schools and libraries on game design and game development.
This book is a manifesto urging deeper thought about what we design as well as how and why we design. As design thinking deepens, its reach widens, making this a book not just for designers but also for policymakers, government ministers, company CEOs and other makers-of-big-decisions. The world we live in presents a myriad of complex, critical challenges which design thinking has the potential to resolve. The hope in writing this book is that when future generations look back and reflect on how we succeeded in steering away from our climate-warming, species-killing, polluting habits of the past towards a more productive, life-fulfilling and equitable future, they might see the hand of deep design thinking on the tiller. Seaton and Mike Baxter are father and son who have both been Professors of Design and have contributed, over several decades between them, to the fields of ecological design, product design and strategy design. This book is the result of many years of discussions between them on the nature of design and the ideas and practicalities that lead to deep design thinking.
The Game Design Deep Dive series examines a specific game system or mechanic over the course of the history of the industry. This entry will examine the history and design of the horror genre and elements in video games. The author analyzes early video game examples, including the differences between survival, action-horror, and psychological horror. Thanks to recent hits like Five Night’s at Freddy’s, Bendy and the Ink Machine, and recent Resident Evil titles, the horror genre has seen a strong resurgence. For this book in the Game Design Deep Dive series, Joshua Bycer will go over the evolution of horror in video games and game design, and what it means to create a terrifying and chilling experience. FEATURES • Written for anyone interested in the horror genre, anyone who wants to understand game design, or anyone simply curious from a historical standpoint • Includes real game examples to highlight the discussed topics and mechanics • Explores the philosophy and aspects of horror that can be applied to any medium • Serves as a perfect companion for someone building their first game or as part of a game design classroom Joshua Bycer is a game design critic with more than eight years of experience critically analyzing game design and the industry itself. In that time, through Game-Wisdom, he has interviewed hundreds of game developers and members of the industry about what it means to design video games. He also strives to raise awareness about the importance of studying game design by giving lectures and presentations. His first book was 20 Essential Games to Study. He continues to work on the Game Design Deep Dive series.
This booklet takes portfolio design beyond the familiar "black box" mean-variance framework. Most importantly, the short-term volatility of financial assets, commonly measured as standard deviation, is a highly imperfect measure of the actual long-horizon perils faced by real-world investors subject to the vagaries of financial and military history. These risks have names--inflation, deflation, confiscation, and devastation--and any useful discussion of portfolio design of necessity incorporates their probabilities, consequences, and costs of mitigation ... This booklet contains ... with luck, a framework within income and all-equity portfolios. This booklet contains ... with luck, a framework within which to think more clearly about risk. Note: the entire Investing for Adults series is not for beginners.
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can use in a wide range of fields, from biology to computer vision to business. With nine in-depth case studies, this book will ground you in creative, real-world deep learning thinking. You’ll begin with a structured guide to using Keras, with helpful tips and best practices for making the most of the framework. Next, you’ll learn how to train models effectively with transfer learning and self-supervised pre-training. You will then learn how to use a variety of model compressions for practical usage. Lastly, you will learn how to design successful neural network architectures and creatively reframe difficult problems into solvable ones. You’ll learn not only to understand and apply methods successfully but to think critically about it. Modern Deep Learning Design and Methods is ideal for readers looking to utilize modern, flexible, and creative deep-learning design and methods. Get ready to design and implement innovative deep-learning solutions to today’s difficult problems. What You’ll Learn Improve the performance of deep learning models by using pre-trained models, extracting rich features, and automating optimization. Compress deep learning models while maintaining performance. Reframe a wide variety of difficult problems and design effective deep learning solutions to solve them. Use the Keras framework, with some help from libraries like HyperOpt, TensorFlow, and PyTorch, to implement a wide variety of deep learning approaches. Who This Book Is For Data scientists with some familiarity with deep learning to deep learning engineers seeking structured inspiration and direction on their next project. Developers interested in harnessing modern deep learning methods to solve a variety of difficult problems.