python for data science
Are you looking for a beginners guide?Do you want to learn how to use python for beginners in a simple way?Do you want to enter into the new world of Python for beginners in an efficient and effective way? This book will teach you the basics as well as the advanced concepts of computers and programming. The gaming industry is growing rapidly and Python offers a lot of libraries to create games. Many tech giants rely on Python to deliver world-class applications.In This book you will learn: Python setupAnacondaWinpythonData science packegesJupyterData munging with pandasThe processImporting datasetsData preprocessingThe data science pipelinePrincipal component analysisSupervised learning algorithmsAnalyzing big dataNeural networks structuresClassification and regression treesThe overfitting problemNew featuresNa簿ve bayes classifierLinear regressionLogistic regressionSupport vector machineApplications in the real worldPruningData selection This book is not just a startup guide. This book will prove beneficial for years to come. The book has the latest codes and techniques so you can equip your skills according to the current market challenges. After all, the purpose is to land a nicely paid job in a globally recognized firm. This book will help you reach that goal!Most people can learn how to code but not just anyone can code smartly. This book is going to help you to think out of the box and take on problems with a completely different perspective. The tricks mentioned will make you invaluable to any software development firm.
python for beginners
Are you looking for a beginner's guide?Do you want to learn how to use python for beginners in a simple way?Do you want to enter into the new world of Python data science as a beginner in an efficient and effective way? This book will teach you the basics as well as the advanced concepts of computers and programming. The gaming industry is growing rapidly and Python offers a lot of libraries to create games. Many tech giants rely on Python to deliver world-class applications. In This book you will learn: ● Data Analysis● Web Applications● GUI Creation● 2D Game Development● Creating Software Distribution● Creating a 2d game● Basic data analysis● Set up django● Taking control of keyboard and mouse● Excel● Websites● Working with numpy● Mathematical concepts● Shifting gears● Gui for file and computer peripheral control● Game design● Building the game● CSV● Using panda framework● Mouse automation● Keyboard automation● Error typesThis book is not just a startup guide. This book will prove beneficial for years to come. The book has the latest codes and techniques so you can equip your skills according to the current market challenges. After all, the purpose is to land a nicely paid job in a globally recognized firm. This book will help you reach that goal! Most people can learn how to code but not just anyone can code smartly. This book is going to help you to think out of the box and take on problems with a completely different perspective. The tricks mentioned will make you invaluable to any software development firm.Even if you don't have any skills this book help you step by step to achieve your goal.in a few days you will be able to learn it.
ACSL Contests 2019-2020
This book presents the 2019-2020 contests organized by the American Computer Science League. ACSL offers 5 divisions to appeal to the variety of abilities of middle school and high school students. Contests consist of two parts: short problems that cover fundamental concepts in computer science and a programming problem, where students solve a specific problem by writing a computer program in a language of their choice. The fundamental computer science topics covered in the short problem tests include Assembly Language Programming, Bit-String Flicking, Boolean Algebra, Computer Number Systems, Data Structures, Digital Electronics, FSAs and Regular Expressions, Graph Theory, LISP, Prefix/Infix/Postfix Notation, Recursive Functions, and What Does This Program Do? There were four regular season contests, held at each participating school. At the end of the season, the top students were invited to participate in an online all-star competition. This book is organized contest by contest. In each contest, the problems and solutions are organized by division.
Python 201
This book is a sequel to Python 101. It will help you grow in your abilities as a Python programmer as it introduces intermediate and advanced topics such as function overloading, Unicode, caching, benchmarking, testing, concurrency and much more!
Google Analytics Kickstarter Guide
Leverage Google Analytics to make data-driven decisions to shape your marketing strategy Key FeaturesLearn how to navigate the Google Analytics interface and reports. Understand the working of the Google Analytics platform. Understanding 'Traffic Sources' in Google Analytics. Learn how to use Segments in Google Analytics. Understand how Cross-Device reporting works in Google Analytics.DescriptionThis book will help you learn everything that you need to know about Google Analytics. We will start by setting up the account and updating the settings. Then, we will go through the main reports in Google Analytics will dive deep into the analysis. We will then analyze the users, their behavior, and their sources. This analysis will improve your business and website results. We will also go through the fundamentals of relating Google Analytics data to your marketing strategy. We will explore live examples of analysis with real Ecommerce data and learn approaches to analyze our data. At the end of the book, we will go through the Conversions section in Google Analytics. By the end of the book, you will be able to make informative decisions based on data related to your website visitors. What will you learn Learn how to set-up a Google Analytics account. Understand how to read all the reports in Google Analytics. Perform complex analysis based on the data in the reports. Learn how to relate the Google Analytics data to your marketing strategy.Read and analyze Conversion reports based on real Ecommerce data. Who this book is for This book is designed for business owners and webmasters who want to use Google Analytics to make better decisions and improve their sales. Table of Contents 1. Google Analytics Step-by-step setup.2. Google Analytics reports explained.3. 7P's of Marketing and Google Analytics.4. Your audience - your business.5. The heartbeat of the Google Analytics: Acquisition & Behavior Reports.6. Conversions. The final goal.About the Author Grigor Yovov is a certified Google Ads and Google Analytics expert and a bachelor in Marketing. He has over 20,000 students from 153 countries in the world's biggest learning platform Udemy, where he creates courses related to Google Ads, Google Analytics and Business Development. In 2011 he founded his own digital marketing agency called Business Trend serving clients all around the world. Your Blog links: http: //howtoads.com/Your LinkedIn Profile: linkedin.com/in/grigor-yovov-digital-marketer
Topics in Theoretical Computer Science
This book constitutes the refereed proceedings of the Third IFIP WG 1.8 International Conference on Topics in Theoretical Computer Science, TTCS 2020, held in Tehran, Iran, in July 2020. The conference was held virtually due to the COVID-19 pandemic. The 8 papers presented in this volume were carefully reviewed and selected from 24 submissions. They focus on novel and high-quality research in all areas of theoretical computer science, such as algorithms and complexity; logic, semantics, and programming theory; and more.
Risks of Artificial Intelligence
Featuring contributions from leading experts and thinkers in the theory of artificial intelligence (AI), this is one of the first books dedicated to examining the risks of AI. The book evaluates predictions of the future of AI, proposes ways to ensure that AI systems will be beneficial to humans, and then critically evaluates such proposals. The
Handbook of Approximation Algorithms and Metaheuristics
This book reflects the tremendous growth in the field over the past two decades. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in emerging applications.
Machine Learning
Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This book provides a more practical approach by explaining the concepts of machine learning algorithms and desc
New Directions in Behavioral Biometrics
Automatic biometrics recognition techniques are increasingly important in corporate and public security systems and have increased in methods due to rapid field development. This book discusses classic behavioral biometrics as well as collects the latest advances in techniques, theoretical approaches, and dynamic applications. This future-lookin
Artificial IntelligenceWith an Introduction to Machine Learning, Second Edition
The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update retains the same accessibility and problem-solving approach, while providing new material and methods, including neural networks and deep learning.
Computer Simulation
This book introduces the fundamentals of computer simulation using Python. Monte Carlo methods and applications are covered extensively, along with advanced topics, such as event graphs and the design of experiments.
Visual Tracking in Conventional Minimally Invasive Surgery
The book takes a step-by-step approach to designing and developing various tools for surgeon computer interfaces using the conventional surgical set-up. Tracking of surgical tools is defined as the key component for developing such interfaces. Using a theoretical basis, the book presents practical implementation for developing visual tracking of
Modern Directional Statistics
This book provides a detailed account on some of the newest methods for dealing with directional data. Directional data naturally arises in diverse domains such as earth sciences (in particular geology), meteorology, astronomy, studies of animal behavior, image analysis, neurosciences, medicine, machine learning, bioinformatics, and cosmology.
Arduino-Based Embedded Systems
This book will help beginners to get started with Arduino-based embedded systems including essential know-how of the programming and interfacing of the devicesbased on practical case studies. It comprises of total twenty projects with description, working model of LabVIEW and programming with Arduino IDE.
Information and Communication Technology for Sustainable Development
This book shows how ICT as an　enabler　for all spheres of development can help innovate business processes and operations, and provide faster integration of new technologies into business systems. Focused on sustainability, it addresses strategic approaches to cope with climatic, environmental, and other global risks, and aims to promote
Networks of the Future
This book provides a collection of contributions illustrating the latest research in the areas of future networks, applications, enabling technologies, and implementation issues and challenges. The book encompasses research on emerging areas such as the wireless technologies, software-defined networks, Cloud Computing, IoT, and Big Data.
Handbook of Robust Low-Rank and Sparse Matrix Decomposition
This handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It offers a framework for computer vision applications, including image processing and video surveillance, and describes many methods and algorithms to tackle different formulation proble
Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits
Integrate scikit-learn with various tools such as NumPy, pandas, imbalanced-learn, and scikit-surprise and use it to solve real-world machine learning problemsKey Features Delve into machine learning with this comprehensive guide to scikit-learn and scientific Python Master the art of data-driven problem-solving with hands-on examples Foster your theoretical and practical knowledge of supervised and unsupervised machine learning algorithms Book Description Machine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular among machine learning practitioners. This book serves as a practical guide for anyone looking to provide hands-on machine learning solutions with scikit-learn and Python toolkits. The book begins with an explanation of machine learning concepts and fundamentals, and strikes a balance between theoretical concepts and their applications. Each chapter covers a different set of algorithms, and shows you how to use them to solve real-life problems. You'll also learn about various key supervised and unsupervised machine learning algorithms using practical examples. Whether it is an instance-based learning algorithm, Bayesian estimation, a deep neural network, a tree-based ensemble, or a recommendation system, you'll gain a thorough understanding of its theory and learn when to apply it. As you advance, you'll learn how to deal with unlabeled data and when to use different clustering and anomaly detection algorithms. By the end of this machine learning book, you'll have learned how to take a data-driven approach to provide end-to-end machine learning solutions. You'll also have discovered how to formulate the problem at hand, prepare required data, and evaluate and deploy models in production. What you will learn Understand when to use supervised, unsupervised, or reinforcement learning algorithms Find out how to collect and prepare your data for machine learning tasks Tackle imbalanced data and optimize your algorithm for a bias or variance tradeoff Apply supervised and unsupervised algorithms to overcome various machine learning challenges Employ best practices for tuning your algorithm's hyper parameters Discover how to use neural networks for classification and regression Build, evaluate, and deploy your machine learning solutions to production Who this book is for This book is for data scientists, machine learning practitioners, and anyone who wants to learn how machine learning algorithms work and to build different machine learning models using the Python ecosystem. The book will help you take your knowledge of machine learning to the next level by grasping its ins and outs and tailoring it to your needs. Working knowledge of Python and a basic understanding of underlying mathematical and statistical concepts is required.
Handbook of Approximation Algorithms and Metaheuristics
Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, and other metaheuristics.
Introduction to Modeling and Simulation with Matlab(r) and Python
The book introduces the principles of mathematical modeling in science, engineering, and social science as well as basic skills of computer programming. The book is aimed at majors in STEM disciplines that need to understand how to create, analyze, and test mathematical models.
Behavior Trees in Robotics and AI
This is the first book on Behavior Trees (BTs) in robotics and AI.
Pervasive Computing
This book introduces fundamental concepts and theories in pervasive computing as well as its key technologies and applications. It explains how to design and implement pervasive middleware and real application systems, covering nearly all aspects related to pervasive computing. Key technologies in the book include pervasive computing-oriented re
A Beginner’s Guide to Image Preprocessing Techniques
This book emphasizes various image pre-processing methods which are necessary for early extraction of features from the image, leading to improved detection of local and global features. Different approaches for image enrichments and improvements are included that affect feature analysis, depending on how the procedures are employed..
Biomimetic and Biohybrid Systems
This book constitutes the proceedings of the 5th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2016, held in Edinburgh, UK, in July 2016. The 34 full and 27 short papers presented in this volume were carefully reviewed and selected from 63 submissions.The theme of the conference encompasses biomimetic methods for manufacture, repair and recycling inspired by natural processes such as reproduction, digestion, morphogenesis and metamorphosis.
Maschinelles Lernen in AktionEinsteigerbuch f羹r Laien, Schritt-f羹r-Schritt Anleitung f羹r A
Sind Sie auf der Suche nach einem Einsteigerbuch, um sich mit den grundlegenden Konzepten des maschinellen Lernens vertraut zu machen?Mein Buch erkl瓣rt Ihnen die grundlegenden Konzepte auf einfach verst瓣ndliche Weise. Wenn Sie dieses Buch gelesen haben, werden Sie ein solides Verst瓣ndnis f羹r die Grundprinzipien haben, das Ihnen den Schritt zu einem fortgeschritteneren Buch erleichtert, wenn Sie mehr dar羹ber lernen m繹chten.
Arduino Cookbook
Want to create devices that interact with the physical world? This cookbook is perfect for anyone who wants to experiment with the popular Arduino microcontroller and programming environment. You'll find more than 200 tips and techniques for building a variety of objects and prototypes such as IoT solutions, environmental monitors, location and position-aware systems, and products that can respond to touch, sound, heat, and light. Updated for the Arduino 1.8 release, the recipes in this third edition include practical examples and guidance to help you begin, expand, and enhance your projects right away--whether you're an engineer, designer, artist, student, or hobbyist. Get up to speed on the Arduino board and essential software concepts quickly Learn basic techniques for reading digital and analog signals Use Arduino with a variety of popular input devices and sensors Drive visual displays, generate sound, and control several types of motors Connect Arduino to wired and wireless networks Learn techniques for handling time delays and time measurement Apply advanced coding and memory-handling techniques
Modern Computer Architecture and OrganizationLearn x86, ARM, and RISC-V architectures and
A no-nonsense, practical guide to current and future processor and computer architectures, enabling you to design computer systems and develop better software applications across a variety of domainsKey Features Understand digital circuitry with the help of transistors, logic gates, and sequential logic Examine the architecture and instruction sets of x86, x64, ARM, and RISC-V processors Explore the architecture of modern devices such as the iPhone X and high-performance gaming PCs Book Description Are you a software developer, systems designer, or computer architecture student looking for a methodical introduction to digital device architectures but overwhelmed by their complexity? This book will help you to learn how modern computer systems work, from the lowest level of transistor switching to the macro view of collaborating multiprocessor servers. You'll gain unique insights into the internal behavior of processors that execute the code developed in high-level languages and enable you to design more efficient and scalable software systems. The book will teach you the fundamentals of computer systems including transistors, logic gates, sequential logic, and instruction operations. You will learn details of modern processor architectures and instruction sets including x86, x64, ARM, and RISC-V. You will see how to implement a RISC-V processor in a low-cost FPGA board and how to write a quantum computing program and run it on an actual quantum computer. By the end of this book, you will have a thorough understanding of modern processor and computer architectures and the future directions these architectures are likely to take. What you will learn Get to grips with transistor technology and digital circuit principles Discover the functional elements of computer processors Understand pipelining and superscalar execution Work with floating-point data formats Understand the purpose and operation of the supervisor mode Implement a complete RISC-V processor in a low-cost FPGA Explore the techniques used in virtual machine implementation Write a quantum computing program and run it on a quantum computer Who this book is for This book is for software developers, computer engineering students, system designers, reverse engineers, and anyone looking to understand the architecture and design principles underlying modern computer systems from tiny embedded devices to warehouse-size cloud server farms. A general understanding of computer processors is helpful but not required.
Machine Learning for IOS Developers
Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple's ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book's clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models--both pre-trained and user-built--with Apple's CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming Develop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.
Glsvlsi ’19
Welcome to the 29th edition of the Great Lakes Symposium on VLSI (GLSVLSI) 2019, held between May 9-11, 2019 at Tysons Corner, VA in the Washington, DC metropolitan area. GLSVLSI is a premier venue for the dissemination of manuscripts of the highest quality in all areas related to VLSI, devices, and system-level design. The location of this year's GLSVLSI is Washington, DC, visiting the east coast of the US, not too far from the "Great Lakes" region of the USA, especially given the global stretch of GLSVLSI host cities within the past decade. Conference will be held at Tysons Corner Marriott located in Tysons Corner, VA, a short ride from downtown Washington DC.ACM GLSVLSI 2019 is presented through the collaborative effort of a 15+ member organizing committee with 100+ technical program committee members. The Technical Program Committee Chairs, Tinoosh Mohsenin and Weisheng Zhao, have put together the 2019 installment of the traditionally strong ACM SIGDA GLSVLSI program. The program is structured around the following eight tracks, with GLSVLSI welcoming the International Conference on Microelectronic Systems Education (MSE) for GLSVLSI attendees as one of the tracks in 2019: 1. VLSI Design (Track Chairs Selcuk Kose, Inna Partin-Vaisband) 2. VLSI Circuits and Power Aware Design (Track Chairs Deliang Fan, Swaroop Ghosh) 3. Computer-Aided Design (Track Chairs Yanzhi Wang, Jianlei Yang) 4. Testing, Reliability, Fault Tolerance (Track Chairs Sandip Ray, Benjamin Schaefer) 5. Emerging Computing & Post-CMOS Technologies (Track Chairs Sorin Cotofana, Yue Zhang) 6. Hardware Security (Track Chairs JV Rajendran, Patrick Schaumont) 7. VLSI for Machine Learning and Artificial Intelligence (Track Chairs Philip Brisk, Amey Kulkarni) 8. Microelectronics Systems Education (Track Chairs Tina Hudson, Bradley Minch)
Machine Learning
If you're at the beginner stage and are looking to gain new knowledge about machine learning then keep reading...WARNING: Do not read this book if you're looking for a boring textbook containing a lot of dry math and programming lingo.Every day, someone is putting down a book on machine learning and giving up on learning about this revolutionary topic.How many of them miss out on furthering their career, and perhaps even the progress of our species...without even realizing?You see, most beginners make the same mistake when first delving into the topic of machine learning.They start off with a resource containing too many unrelatable facts, math, and programming lingo that will put them to sleep rather than ignite their passion.But that is about to change...This new book on machine learning will explain the concepts, methods and history behind machine learning, including how our computers became vastly more powerful but infinitely stupider than ever before and why every tech company and their grandmother want to keep track of us 24/7, siphoning data points from our electronic devices to be crunched by their programs that then become virtual crystal balls, predicting our thoughts before we even have them.Most of the book reads like science fiction because in a sense it is, far beyond what an average person would be willing to believe is happening.Here are some of the topics that are discussed in this book: What is machine learning? What's the point of machine learning? History of machine learning Neural networks Matching the human brain Artificial Intelligence AI in literature Talking, walking robots Self-driving cars Personal voice-activated assistants Data mining Social networks Big Data Shadow profiles Biometrics Self-replicating machines And much, much more! So if you want a book on machine learning that can cause some people to scream for more as oppose to falling asleep, click "add to cart"!
Machine Learning
3 comprehensive manuscripts in 1 book Machine Learning: An Essential Guide to Machine Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More Neural Networks: An Essential Beginners Guide to Artificial Neural Networks and their Role in Machine Learning and Artificial Intelligence Deep Learning: An Essential Guide to Deep Learning for Beginners Who Want to Understand How Deep Neural Networks Work and Relate to Machine Learning and Artificial Intelligence Every day, someone is putting down a book on machine learning and giving up on learning about this revolutionary topic. How many of them miss out on furthering their career, and perhaps even the progress of our species...without even realizing? You see, most beginners make the same mistake when first delving into the topic of machine learning. They start off with a resource containing too many unrelatable facts, math, and programming lingo that will put them to sleep rather than ignite their passion. But that is about to change... This new book on machine learning will explain the concepts, methods and history behind machine learning, including how our computers became vastly more powerful but infinitely stupider than ever before and why every tech company and their grandmother want to keep track of us 24/7, siphoning data points from our electronic devices to be crunched by their programs that then become virtual crystal balls, predicting our thoughts before we even have them. Most of the book reads like science fiction because in a sense it is, far beyond what an average person would be willing to believe is happening. Here are some of the topics that are discussed in part 1 of this book: What is machine learning? What's the point of machine learning? History of machine learning Neural networks Matching the human brain Artificial Intelligence AI in literature Talking, walking robots Self-driving cars Personal voice-activated assistants Data mining Social networks Big Data Shadow profiles Biometrics Self-replicating machines And much, much more! Here are some of the topics that are discussed in part 2 of this book: Programming a smart(er) computer Composition Giving neural networks legs to stand on The magnificent wetware Personal assistants Tracking users in the real world Self-driving neural networks Taking everyone's job Quantum leap in computing Attacks on neural networks Neural network war Ghost in the machine No backlash And Much, Much More Here are some of the topics that are discussed in part 3 of this book: Improving the Scientific Method How It All Started Appeasing the Rebellious Spirits Quantum Approach To Science The Replication Crisis Evolving the Machine Brain The Future of Deep Learning Medicine with the Help of a Digital Genie And Much, Much More So if you want to learn about machine learning, click "buy now"!
Machine Learning in the Aws Cloud
Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem.
Machine Beauty
When something works well, you can feel it; there is a sense of rightness to it. We call that rightness beauty, and it ought to be the single most important component of design.This recognition is at the heart of David Gelernter's witty argued essay, Machine Beauty, which defines beauty as an inspired mating of simplicity and power. You can see it in a Bauhaus chair, the Hoover Dam, or an Emerson radio circa 1930. In contrast, too many contemporary technologists run out of ideas and resort to gimmicks and features; they are rarely capable of real, structural ingenuity.Nowhere is this more evident than in the world of computers. You don't have to look far to see how oblivious most computer technologists are to the idea of beauty. Just look at how ugly your computer cabinet is, how unwieldy and out of sync it feels with the manner and speed with which you process thought.The best designers, however, are obsessed with beauty. Both hardware and software should afford us the greatest opportunity to achieve deep beauty, the kind of beauty that happens when many types of loveliness reinforce one another, when design expresses an underlying technology, a machine logic. Program software ought to be transparent; it should engage what Gelernter calls "a thought-amplifying feedback loop," a creative symbiosis with its user. These principles, beautiful in themselves, will set the stage for the next technological revolution, in which the pursuit of elegance will lead to extraordinary innovations.Machine Beauty will delight Gelernter's growing audience, fans of his provocative and biting journalism. Anyone who manufactures, designs, or uses computers will be galvanized by his cogent arguments and tantalizing glimpse of a bright future, where beautiful technology abounds.
Arduino in a Nutshell
Rather than yet another project-based workbook, Arduino: A Technical Reference is a reference and handbook that thoroughly describes the electrical and performance aspects of an Arduino board and its software. This book brings together in one place all the information you need to get something done with Arduino. It will save you from endless web searches and digging through translations of datasheets or notes in project-based texts to find the information that corresponds to your own particular setup and question. Reference features include pinout diagrams, a discussion of the AVR microcontrollers used with Arduino boards, a look under the hood at the firmware and run-time libraries that make the Arduino unique, and extensive coverage of the various shields and add-on sensors that can be used with an Arduino. One chapter is devoted to creating a new shield from scratch. The book wraps up with detailed descriptions of three different projects: a programmable signal generator, a "smart" thermostat, and a programmable launch sequencer for model rockets. Each project highlights one or more topics that can be applied to other applications.
Making Things Move
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Get Your Move On!In Making Things Move: DIY Mechanisms for Inventors, Hobbyists, and Artists, you'll learn how to successfully build moving mechanisms through non-technical explanations, examples, and do-it-yourself projects--from kinetic art installations to creative toys to energy-harvesting devices. Photographs, illustrations, screen shots, and images of 3D models are included for each project. This unique resource emphasizes using off-the-shelf components, readily available materials, and accessible fabrication techniques. Simple projects give you hands-on practice applying the skills covered in each chapter, and more complex projects at the end of the book incorporate topics from multiple chapters. Turn your imaginative ideas into reality with help from this practical, inventive guide. Discover how to: Find and select materialsFasten and join partsMeasure force, friction, and torqueUnderstand mechanical and electrical power, work, and energyCreate and control motionWork with bearings, couplers, gears, screws, and springsCombine simple machines for work and funProjects include: Rube Goldberg breakfast machineMousetrap powered carDIY motor with magnet wireMotor direction and speed controlDesigning and fabricating spur gearsAnimated creations in paperAn interactive rotating platformSmall vertical axis wind turbineSADbot: the seasonally affected drawing robotMake Great Stuff!TAB, an imprint of McGraw-Hill Professional, is a leading publisher of DIY technology books for makers, hackers, and electronics hobbyists.
Software Process Dynamics
This book is designed for professionals and students in software engineering or information technology who are interested in understanding the dynamics of software development in order to assess and optimize their own process strategies. It explains how simulation of interrelated technical and social factors can provide a means for organizations to vastly improve their processes. It is structured for readers to approach the subject from different perspectives, and includes descriptive summaries of the best research and applications.
The Supermen
The Supermen offers the first up-close-and-personal profile of Seymour Cray, the brilliant and reputedly eccentric designer of the world's fastest computers. This is the story of a technical genius who, against all odds, created a series of machines that revolutionized the computing industry. Chronicling each major breakthrough, Murray takes us behind the scenes to witness late-night brainstorming sessions, miraculous eleventh-hour fixes, and flashes of insight when bold new ideas were cooked up. Drawing from rare in-depth interviews with Seymour Cray, Murray gives us an unparalleled portrait of the man and his methods, reporting not only Cray's personal reflections, but the recollections of his closest colleagues and the truth behind the rumors.
