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Andrew Glassner's Notebook by Andrew S. Glassner Pdf
This is a collection of 18 columns written by Andrew Glassner for Computer Graphic and Applications magazine. As well as the published material, the book includes notes and corrections to the original articles, a chapter of introduction, and additional text and graphics not originally included. Topics range from computer graphics and art, to the ethics of computers in society.
Andrew Glassner's Other Notebook by Andrew Glassner Pdf
Once again, Andrew Glassner opens his notebook and invites readers in a wide range of stimulating explorations of art, nature, and computer graphics. The text of this book is accessible and informal, and richly illustrated with hundreds of images illustrating topics from Celtic knotwork and lightning to soap bubbles and the mysteries of camera shutters. This well-known author brings decades of experience as a researcher and writer to create discussions that are as clear as they are captivating. The book is intended for hobbyists, researchers, students, and anyone interested in computer graphics and its uses for creative exploration.
Andrew Glassner's Other Notebook by Andrew Glassner Pdf
Once again, Andrew Glassner opens his notebook and invites readers in a wide range of stimulating explorations of art, nature, and computer graphics. The text of this book is accessible and informal, and richly illustrated with hundreds of images illustrating topics from Celtic knotwork and lightning to soap bubbles and the mysteries of camera shutters. This well-known author brings decades of experience as a researcher and writer to create discussions that are as clear as they are captivating. The book is intended for hobbyists, researchers, students, and anyone interested in computer graphics and its uses for creative exploration.
A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human activities, from writing songs and generating news articles to helping doctors provide healthcare. Deep learning is the source of many of these breakthroughs, and its remarkable ability to find patterns hiding in data has made it the fastest growing field in artificial intelligence (AI). Digital assistants on our phones use deep learning to understand and respond intelligently to voice commands; automotive systems use it to safely navigate road hazards; online platforms use it to deliver personalized suggestions for movies and books - the possibilities are endless. Deep Learning: A Visual Approach is for anyone who wants to understand this fascinating field in depth, but without any of the advanced math and programming usually required to grasp its internals. If you want to know how these tools work, and use them yourself, the answers are all within these pages. And, if you're ready to write your own programs, there are also plenty of supplemental Python notebooks in the accompanying Github repository to get you going. The book's conversational style, extensive color illustrations, illuminating analogies, and real-world examples expertly explain the key concepts in deep learning, including: • How text generators create novel stories and articles • How deep learning systems learn to play and win at human games • How image classification systems identify objects or people in a photo • How to think about probabilities in a way that's useful to everyday life • How to use the machine learning techniques that form the core of modern AI Intellectual adventurers of all kinds can use the powerful ideas covered in Deep Learning: A Visual Approach to build intelligent systems that help us better understand the world and everyone who lives in it. It's the future of AI, and this book allows you to fully envision it. Full Color Illustrations
Quantum Computer Science by Marco Lanzagorta,Jeffrey Uhlmann Pdf
In this text we present a technical overview of the emerging field of quantum computation along with new research results by the authors. What distinguishes our presentation from that of others is our focus on the relationship between quantum computation and computer science. Specifically, our emphasis is on the computational model of quantum computingrather than on the engineering issues associated with its physical implementation. We adopt this approach for the same reason that a book on computer programming doesn't cover the theory and physical realization of semiconductors. Another distinguishing feature of this text is our detailed discussion of the circuit complexity of quantum algorithms. To the extent possible we have presented the material in a form that is accessible to the computer scientist, but in many cases we retain the conventional physics notation so that the reader will also be able to consult the relevant quantum computing literature. Although we expect the reader to have a solid understanding of linear algebra, we do not assume a background in physics. This text is based on lectures given as short courses and invited presentations around the world, and it has been used as the primary text for a graduatecourse at George Mason University. In all these cases our challenge has been the same: how to present to a generalaudience a concise introduction to the algorithmic structure and applications of quantum computing on an extremely short period of time. The feedback from these courses and presentations has greatly aided in making our exposition of challenging concepts more accessible to a general audience. Table of Contents: Introduction / The Algorithmic Structure of Quantum Computing / Advantages and Limitations of Quantum Computing / Amplitude Amplification / Case Study: Computational Geometry / The Quantum Fourier Transform / Case Study: The Hidden Subgroup / Circuit Complexity Analysis of Quantum Algorithms / Conclusions / Bibliography
Deep Learning Illustrated by Jon Krohn,Grant Beyleveld,Aglaé Bassens Pdf
"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
An Introduction to Ray Tracing by Andrew S. Glassner Pdf
The creation of ever more realistic 3-D images is central to the development of computer graphics. The ray tracing technique has become one of the most popular and powerful means by which photo-realistic images can now be created. The simplicity, elegance and ease of implementation makes ray tracing an essential part of understanding and exploiting state-of-the-art computer graphics. An Introduction to Ray Tracing develops from fundamental principles to advanced applications, providing "how-to" procedures as well as a detailed understanding of the scientific foundations of ray tracing. It is also richly illustrated with four-color and black-and-white plates. This is a book which will be welcomed by all concerned with modern computer graphics, image processing, and computer-aided design. Provides practical "how-to" information Contains high quality color plates of images created using ray tracing techniques Progresses from a basic understanding to the advanced science and application of ray tracing
Morphs, Mallards, and Montages by Andrew Glassner Pdf
This book is for everyone who's interested in computer graphics and how it can take us on exciting journeys powered by imagination and a love of discovery and invention. Each chapter investigates a unique topic and gives you the tools to continue that exploration on your own. Examine the possibilities of: - Pop-up books and cards - Reconstructing shredded documents - Crop circles - Weaves and Tartans - Morphing images and much more! Browse and enjoy the array of visual ideas or roll up your sleeves and write your own code.
Make cool stuff. If you're a designer or artist without a lot of programming experience, this book will teach you to work with 2D and 3D graphics, sound, physical interaction, and electronic circuitry to create all sorts of interesting and compelling experiences -- online and off. Programming Interactivity explains programming and electrical engineering basics, and introduces three freely available tools created specifically for artists and designers: Processing, a Java-based programming language and environment for building projects on the desktop, Web, or mobile phones Arduino, a system that integrates a microcomputer prototyping board, IDE, and programming language for creating your own hardware and controls OpenFrameworks, a coding framework simplified for designers and artists, using the powerful C++ programming language BTW, you don't have to wait until you finish the book to actually make something. You'll get working code samples you can use right away, along with the background and technical information you need to design, program, build, and troubleshoot your own projects. The cutting edge design techniques and discussions with leading artists and designers will give you the tools and inspiration to let your imagination take flight.
Processing for Visual Artists by Andrew Glassner Pdf
Learn how to create gorgeous and expressive imagery with the Processing graphics language and environment. It's easy with this practical, hands-on book. Processing is for artists, designers, visualization creators, hobbyists, or anyone else looking to create images, animation, and interactive pieces for art, education, science, or business. Process
The control of cameras is as important in games as it is in cinema. How the camera tracks and moves determines our point of view and influences our attitude towards the content. A poorly designed camera system in a game can disrupt a users experience, while a well-designed one can make a good game into a great one. The challenge in games is that th
Overcoming Medical Phobias by Martin Antony,Mark Watling Pdf
Overcome Your Fear of Doctors, Blood, Needles, and More-You Can Do It! Does even the thought of a visit to the doctor's office start your heart racing? You're not alone. Some 30 million of us have a significant fear of doctors, dentists, medical procedures, blood, needles, and so forth. These fears might already have inconvenienced you, but if you're avoiding necessary medical attention, you could be putting yourself in great physical danger. But you don't have to live with these fears anymore. This book can help you overcome your medical phobia, maybe in less time that you ever thought possible. Start by learning about your fears, where they might come from, what factors influence them, and how you can best prepare to overcome them. Then you'll gradually and safely confront your specific fears. The book also includes information about avoiding relapse so you can maintain your progress, as well as steps for helping someone you care about who suffers from a medical phobia. Learn about your fears, how they may have begun, and the methods used to treat them Prepare for treatment, either on your own or with the help of a professional Explore exposure-based strategies for overcoming your fears Learn strategies to prevent fainting Plan relapse-prevention strategies to maintain your progress Engage your family and friends as sources of support
NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA "Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us." -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Texturing and Modeling by David S. Ebert,F. Kenton Musgrave,Darwyn Peachey,Ken Perlin,Steve Worley Pdf
The third edition of this classic tutorial and reference on procedural texturing and modeling is thoroughly updated to meet the needs of today's 3D graphics professionals and students. New for this edition are chapters devoted to real-time issues, cellular texturing, geometric instancing, hardware acceleration, futuristic environments, and virtual universes. In addition, the familiar authoritative chapters on which readers have come to rely contain all-new material covering L-systems, particle systems, scene graphs, spot geometry, bump mapping, cloud modeling, and noise improvements. There are many new spectacular color images to enjoy, especially in this edition's full-color format. As in the previous editions, the authors, who are the creators of the methods they discuss, provide extensive, practical explanations of widely accepted techniques as well as insights into designing new ones. New to the third edition are chapters by two well-known contributors: Bill Mark of NVIDIA and John Hart of the University of Illinois at Urbana-Champaign on state-of-the-art topics not covered in former editions. An accompanying Web site (www.texturingandmodeling.com) contains all of the book's sample code in C code segments (all updated to the ANSI C Standard) or in RenderMan shading language, plus files of many magnificent full-color illustrations. No other book on the market contains the breadth of theoretical and practical information necessary for applying procedural methods. More than ever, Texturing & Modeling remains the chosen resource for professionals and advanced students in computer graphics and animation. *New chapters on: procedural real-time shading by Bill Mark, procedural geometric instancing and real-time solid texturing by John Hart, hardware acceleration strategies by David Ebert, cellular texturing by Steven Worley, and procedural planets and virtual universes by Ken Musgrave. *New material on Perlin Noise by Ken Perlin. *Printed in full color throughout. *Companion Web site contains revised sample code and dozens of images.
We are on the verge of creating an exciting new kind of interactive story form that will involve audiences as active participants. This book provides a solid foundation in the fundamentals of classical story structure and classical game structure and explains why it has been surprisingly difficult to bring these two activities together. With this foundation in place, the book presents several ideas for ways to move forward in this appealing quest. The author has a conversational and friendly style, making reading a pleasure.