The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently.
Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.
Thousands of people have had near-death experiences, but scientists have argued that they are impossible. Dr. Eben Alexander was one of those scientists. A highly trained neurosurgeon, Alexander knew that NDEs feel real, but are simply fantasies produced by brains under extreme stress.
Then, Dr. Alexander’s own brain was attacked by a rare illness. The part of the brain that controls thought and emotion—and in essence makes us human—shut down completely. For seven days he lay in a coma. Then, as his doctors considered stopping treatment, Alexander’s eyes popped open. He had come back.
Alexander’s recovery is a medical miracle. But the real miracle of his story lies elsewhere. While his body lay in coma, Alexander journeyed beyond this world and encountered an angelic being who guided him into the deepest realms of super-physical existence. There he met, and spoke with, the Divine source of the universe itself.
Alexander’s story is not a fantasy. Before he underwent his journey, he could not reconcile his knowledge of neuroscience with any belief in heaven, God, or the soul. Today Alexander is a doctor who believes that true health can be achieved only when we realize that God and the soul are real and that death is not the end of personal existence but only a transition.
This story would be remarkable no matter who it happened to. That it happened to Dr. Alexander makes it revolutionary. No scientist or person of faith will be able to ignore it. Reading it will change your life.
This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
The Future of the Mind brings a topic that once belonged solely to the province of science fiction into a startling new reality. This scientific tour de force unveils the astonishing research being done in top laboratories around the world—all based on the latest advancements in neuroscience and physics—including recent experiments in telepathy, mind control, avatars, telekinesis, and recording memories and dreams. The Future of the Mind is an extraordinary, mind-boggling exploration of the frontiers of neuroscience. Dr. Kaku looks toward the day when we may achieve the ability to upload the human brain to a computer, neuron for neuron; project thoughts and emotions around the world on a brain-net; take a “smart pill” to enhance cognition; send our consciousness across the universe; and push the very limits of immortality.
There are many biochemistry textbooks in the market. Some of them are purely basic while others are applied, and there are very few books which cover both these aspects together. For this reason, the students learning biochemistry in their undergraduate courses have to depend on multiple books to acquire a sound knowledge of the subject.
This book, ‘Biochemistry’ is unique with a simultaneous and equal emphasis on basic and applied aspects of biochemistry. This textbook offers an integration of medical and pure sciences, comprehensively written to meet the curriculum requirements of undergraduate courses in medical, dental, pharmacy, life-sciences and other categories (agriculture, veterinary, etc.).
This book is designed to develop in students a sustained interest and enthusiasm to learn and develop the concepts in biochemistry in a logical and stepwise manner. It incorporates a variety of pedagogic aids, besides colour illustrations to help the students understand the subject quickly and to the maximum. The summary and biomedical/clinical concepts are intended for a rapid absorption and assimilation of the facts and concepts in biochemistry. The self-assessment exercises will stimulate the students to think rather than merely learn the subject. In addition, these exercises (essays, short notes, fill in the blanks, multiple choice questions) set at different difficulty levels, will cater to the needs of all the categories of learners.
New to This Edition
The book offers an integration of medical and pure sciences, and is comprehensively written, revised and updated to meet the curriculum requirements of Medical, Pharmacy, Dental, Veterinary, Biotechnology, Agricultural Sciences, Life Sciences, and others studying Biochemistry as one of the subjects.
It is the first text book on Biochemistry in English with multi-colour illustrations by an author from Asia. The use of multicolours is for a clearer understanding of the complicated biochemical reactions.
It is written in a lucid style with the subject being presented as an engaging story growing from elementary information to the most recent advances, and with theoretical discussions being supplemented with illustrations, flowcharts, and tables for easy understanding of Biochemistry.
It has each chapter beginning with a four-line verse followed by the text, biomedical concepts, a summary, and self-assessment exercises. The lively illustrations and text with appropriate headings and sub-headings in bold type faces facilitate reading path clarity and quick recall.
It provides the most recent and essential information on Molecular Biology and Biotechnology, Diabetes, Cancer, Free Radicals, Free radicals and Antioxidants, Prostaglandins, etc.
It describes a wide variety of case studies and biochemical correlations and several newer biomedical aspects- Metabolic syndrome, Therapeutic diets, Atkins diet, Trans fatty acids, Epigenetics, Nutrigenomics, Recombinant ribozymes, Membrane transport disorders, Pleural fluid etc.
It contains the basics (Bioorganic and Biophysical Chemistry, Tools of Biochemistry, Immunology, and Genetics) for beginners to learn easily Biochemistry, origins of biochemical words, confusables in Biochemistry, principles of Practical Biochemistry, and Clinical Biochemistry Laboratory.
An instant bestseller that is poised to become a classic, Moonwalking with Einstein recounts Joshua Foer's yearlong quest to improve his memory under the tutelage of top "mental athletes." He draws on cutting-edge research, a surprising cultural history of remembering, and venerable tricks of the mentalist's trade to transform our understanding of human memory. From the United States Memory Championship to deep within the author's own mind, this is an electrifying work of journalism that reminds us that, in every way that matters, we are the sum of our memories.
From the Trade Paperback edition.
Ray Kurzweil is arguably today’s most influential—and often controversial—futurist. In How to Create a Mind, Kurzweil presents a provocative exploration of the most important project in human-machine civilization—reverse engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines.
Kurzweil discusses how the brain functions, how the mind emerges from the brain, and the implications of vastly increasing the powers of our intelligence in addressing the world’s problems. He thoughtfully examines emotional and moral intelligence and the origins of consciousness and envisions the radical possibilities of our merging with the intelligent technology we are creating.
Certain to be one of the most widely discussed and debated science books of the year, How to Create a Mind is sure to take its place alongside Kurzweil’s previous classics which include Fantastic Voyage: Live Long Enough to Live Forever and The Age of Spiritual Machines.
From the Hardcover edition.
Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself.
Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines.
The brain is not a computer, but a memory system that stores experiences in a way that reflects the true structure of the world, remembering sequences of events and their nested relationships and making predictions based on those memories. It is this memory-prediction system that forms the basis of intelligence, perception, creativity, and even consciousness.
In an engaging style that will captivate audiences from the merely curious to the professional scientist, Hawkins shows how a clear understanding of how the brain works will make it possible for us to build intelligent machines, in silicon, that will exceed our human ability in surprising ways.
Written with acclaimed science writer Sandra Blakeslee, On Intelligence promises to completely transfigure the possibilities of the technology age. It is a landmark book in its scope and clarity.
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.
Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approach
Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details
In contrast to the “baseline brain” that fulfills the tasks of everyday life, Chopra and Tanzi propose that, through a person’s increased self-awareness and conscious intention, the brain can be taught to reach far beyond its present limitations. “We are living in a golden age for brain research, but is this a golden age for your brain?” they ask.
Super Brain explains how it can be, by combining cutting-edge research and spiritual insights, demolishing the five most widespread myths about the brain that limit your potential, and then showing you methods to:
-Use your brain instead of letting it use you
-Create the ideal lifestyle for a healthy brain
-Reduce the risks of aging
-Promote happiness and well-being through the mind-body connection
-Access the enlightened brain, the gateway to freedom and bliss
-Overcome the most common challenges, such as memory loss, depression, anxiety, and obesity
Your brain is capable of incredible healing and constant reshaping. Through a new relationship with your brain you can transform your life. In Super Brain, Chopra and Tanzi guide you on a fascinating journey that envisions a leap in human evolution. The brain is not just the greatest gift that Nature has given us. It’s the gateway to an unlimited future that you can begin to live today.
Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
On December 10, 1996, Jill Bolte Taylor, a thirty-seven- year-old Harvard-trained brain scientist experienced a massive stroke in the left hemisphere of her brain. As she observed her mind deteriorate to the point that she could not walk, talk, read, write, or recall any of her life-all within four hours-Taylor alternated between the euphoria of the intuitive and kinesthetic right brain, in which she felt a sense of complete well-being and peace, and the logical, sequential left brain, which recognized she was having a stroke and enabled her to seek help before she was completely lost. It would take her eight years to fully recover.
For Taylor, her stroke was a blessing and a revelation. It taught her that by "stepping to the right" of our left brains, we can uncover feelings of well-being that are often sidelined by "brain chatter." Reaching wide audiences through her talk at the Technology, Entertainment, Design (TED) conference and her appearance on Oprah's online Soul Series, Taylor provides a valuable recovery guide for those touched by brain injury and an inspiring testimony that inner peace is accessible to anyone.
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.Get started quickly with an R tutorial and hundreds of examplesExplore R syntax, objects, and other language detailsFind thousands of user-contributed R packages online, including BioconductorLearn how to use R to prepare data for analysisVisualize your data with R’s graphics, lattice, and ggplot2 packagesUse R to calculate statistical fests, fit models, and compute probability distributionsSpeed up intensive computations by writing parallel R programs for HadoopGet a complete desktop reference to R
Imaging Informatics Professionals (IIPs) have come to play an indispensable role in modern medicine, and the scope of this profession has grown far beyond the boundaries of the PACS. A successful IIP must not only understand the PACS itself, but also have knowledge of clinical workflow, a base in several medical specialties, and a solid IT capability regarding software interactions and networking. With the introduction of a certification test for the IIP position, a single source was needed to explain the fundamentals of imaging informatics and to demonstrate how those fundamentals are applied in everyday practice. Practical Imaging Informatics describes the foundations of information technology and clinical image management, details typical daily operations, and discusses rarer complications and issues.
Each chapter ends with clinical cases and the related questions, which evokes yet another method of active learning rather than didactic methods of imparting knowledge.
Key points have been highlighted and boxed at the end of each topic for quick revision of the core concepts.
This book comes with a free companion website which contains self-assessment exercises, detailed case discussions related to the clinical cases given inside the book, glossary and various other features for enhanced learning.
This book is dedicated to all the machine learning and deep learning enthusiasts, data scientists, researchers, and even students who want to perform more accurate, fast machine learning operations with TensorFlow. Those with basic knowledge of programming (Python and C/C++) and math concepts who want to be introduced to the topics of machine learning will find this book useful.What You Will LearnInstall and adopt TensorFlow in your Python environment to solve mathematical problemsGet to know the basic machine and deep learning conceptsTrain and test neural networks to fit your data modelMake predictions using regression algorithmsAnalyze your data with a clustering procedureDevelop algorithms for clustering and data classificationUse GPU computing to analyze big dataIn Detail
Google's TensorFlow engine, after much fanfare, has evolved in to a robust, user-friendly, and customizable, application-grade software library of machine learning (ML) code for numerical computation and neural networks.
This book takes you through the practical software implementation of various machine learning techniques with TensorFlow. In the first few chapters, you'll gain familiarity with the framework and perform the mathematical operations required for data analysis. As you progress further, you'll learn to implement various machine learning techniques such as classification, clustering, neural networks, and deep learning through practical examples.
By the end of this book, you'll have gained hands-on experience of using TensorFlow and building classification, image recognition systems, language processing, and information retrieving systems for your application.Style and approach
Get quickly up and running with TensorFlow using this fast-paced guide. You will get to know everything that can be done with TensorFlow and we'll show you how to implement it in your environment. The examples in the book are from the core of the computation industry—something you can connect to and will find familiar.
Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data.
Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time.
Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book includes:A thorough introduction to OpenCVGetting input from camerasTransforming imagesSegmenting images and shape matchingPattern recognition, including face detectionTracking and motion in 2 and 3 dimensions3D reconstruction from stereo visionMachine learning algorithms
Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.
R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.
Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.
You’ll learn how to:Wrangle—transform your datasets into a form convenient for analysisProgram—learn powerful R tools for solving data problems with greater clarity and easeExplore—examine your data, generate hypotheses, and quickly test themModel—provide a low-dimensional summary that captures true "signals" in your datasetCommunicate—learn R Markdown for integrating prose, code, and results
This book will help you:Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification
Corresponding data sets are available at www.wiley.com/go/9781118876138.
Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
Chances are you already use Excel to perform some fairly routine calculations. Now the Excel Scientific and Engineering Cookbook shows you how to leverage Excel to perform more complex calculations, too, calculations that once fell in the domain of specialized tools. It does so by putting a smorgasbord of data analysis techniques right at your fingertips. The book shows how to perform these useful tasks and others:Use Excel and VBA in generalImport data from a variety of sourcesAnalyze dataPerform calculationsVisualize the results for interpretation and presentationUse Excel to solve specific science and engineering problems
Wherever possible, the Excel Scientific and Engineering Cookbook draws on real-world examples from a range of scientific disciplines such as biology, chemistry, and physics. This way, you'll be better prepared to solve the problems you face in your everyday scientific or engineering tasks.
High on practicality and low on theory, this quick, look-up reference provides instant solutions, or "recipes," to problems both basic and advanced. And like other books in O'Reilly's popular Cookbook format, each recipe also includes a discussion on how and why it works. As a result, you can take comfort in knowing that complete, practical answers are a mere page-flip away.
With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you’ve learned.
This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision.Learn OpenCV data types, array types, and array operationsCapture and store still and video images with HighGUITransform images to stretch, shrink, warp, remap, and repairExplore pattern recognition, including face detectionTrack objects and motion through the visual fieldReconstruct 3D images from stereo visionDiscover basic and advanced machine learning techniques in OpenCV
When Temple Grandin was born in 1947, autism had only just been named. Today it is more prevalent than ever, with one in 88 children diagnosed on the spectrum. And our thinking about it has undergone a transformation in her lifetime: Autism studies have moved from the realm of psychology to neurology and genetics, and there is far more hope today than ever before thanks to groundbreaking new research into causes and treatments. Now Temple Grandin reports from the forefront of autism science, bringing her singular perspective to a thrilling journey into the heart of the autism revolution.
Weaving her own experience with remarkable new discoveries, Grandin introduces the neuroimaging advances and genetic research that link brain science to behavior, even sharing her own brain scan to show us which anomalies might explain common symptoms. We meet the scientists and self-advocates who are exploring innovative theories of what causes autism and how we can diagnose and best treat it. Grandin also highlights long-ignored sensory problems and the transformative effects we can have by treating autism symptom by symptom, rather than with an umbrella diagnosis. Most exciting, she argues that raising and educating kids on the spectrum isn’t just a matter of focusing on their weaknesses; in the science that reveals their long-overlooked strengths she shows us new ways to foster their unique contributions.
From the “aspies” in Silicon Valley to the five-year-old without language, Grandin understands the true meaning of the word spectrum. The Autistic Brain is essential reading from the most respected and beloved voices in the field.
Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples with explanations on how to reproduce and build upon each example, along with exercises to help you apply what you’ve learned. This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills.Learn techniques used in robot navigation, medical image analysis, and other computer vision applicationsWork with image mappings and transforms, such as texture warping and panorama creationCompute 3D reconstructions from several images of the same sceneOrganize images based on similarity or content, using clustering methodsBuild efficient image retrieval techniques to search for images based on visual contentUse algorithms to classify image content and recognize objectsAccess the popular OpenCV library through a Python interface
Growing up in the high desert of California, Jim Doty was poor, with an alcoholic father and a mother chronically depressed and paralyzed by a stroke. Today he is the director of the Center for Compassion and Altruism Research and Education (CCARE) at Stanford University, of which the Dalai Lama is a founding benefactor. But back then his life was at a dead end until at twelve he wandered into a magic shop looking for a plastic thumb. Instead he met Ruth, a woman who taught him a series of exercises to ease his own suffering and manifest his greatest desires. Her final mandate was that he keep his heart open and teach these techniques to others. She gave him his first glimpse of the unique relationship between the brain and the heart.
Doty would go on to put Ruth’s practices to work with extraordinary results—power and wealth that he could only imagine as a twelve-year-old, riding his orange Sting-Ray bike. But he neglects Ruth’s most important lesson, to keep his heart open, with disastrous results—until he has the opportunity to make a spectacular charitable contribution that will virtually ruin him. Part memoir, part science, part inspiration, and part practical instruction, Into the Magic Shop shows us how we can fundamentally change our lives by first changing our brains and our hearts.
It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.
This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision.Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth EditionSolved examples in Matlab, including real-life data sets in imaging and audio recognitionAvailable separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)
The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other.
How many times have you seen a murder on the news or on a TV show like CSI: Crime Scene Investigation, and said to yourself, “How could someone do something like that?”
Today, neuroscientists are imaging, mapping, testing and dissecting the source of the worst behavior imaginable in the brains of the people who lack a conscience: psychopaths. Neuroscientist Dean Haycock examines the behavior of real life psychopaths and discusses how their actions can be explained in scientific terms, from research that literally looks inside their brains to understanding how psychopaths, without empathy but very goal-oriented, think and act the way they do. Some don’t commit crimes at all, but rather make use of their skills in the boardroom.
But what does this mean for lawyers, judges, psychiatrists, victims, and readers—for anyone who has ever wondered how some people can be so bad. Could your nine-year-old be a psychopath? What about your co-worker? The ability to recognize psychopaths using the scientific method has vast implications for society, and yet is still loaded with consequences.
Winner of the National Academy of Sciences Best Book Award in 2012
Selected by the New York Times Book Review as one of the ten best books of 2011
A Globe and Mail Best Books of the Year 2011 Title
One of The Economist's 2011 Books of the Year
One of The Wall Street Journal's Best Nonfiction Books of the Year 2011
2013 Presidential Medal of Freedom Recipient
Kahneman's work with Amos Tversky is the subject of Michael Lewis's The Undoing Project: A Friendship That Changed Our Minds
In the international bestseller, Thinking, Fast and Slow, Daniel Kahneman, the renowned psychologist and winner of the Nobel Prize in Economics, takes us on a groundbreaking tour of the mind and explains the two systems that drive the way we think. System 1 is fast, intuitive, and emotional; System 2 is slower, more deliberative, and more logical. The impact of overconfidence on corporate strategies, the difficulties of predicting what will make us happy in the future, the profound effect of cognitive biases on everything from playing the stock market to planning our next vacation—each of these can be understood only by knowing how the two systems shape our judgments and decisions.
Engaging the reader in a lively conversation about how we think, Kahneman reveals where we can and cannot trust our intuitions and how we can tap into the benefits of slow thinking. He offers practical and enlightening insights into how choices are made in both our business and our personal lives—and how we can use different techniques to guard against the mental glitches that often get us into trouble. Winner of the National Academy of Sciences Best Book Award and the Los Angeles Times Book Prize and selected by The New York Times Book Review as one of the ten best books of 2011, Thinking, Fast and Slow is destined to be a classic.
"Seamless R and C++ integration with Rcpp" is simply a wonderful book. For anyone who uses C/C++ and R, it is an indispensable resource. The writing is outstanding. A huge bonus is the section on applications. This section covers the matrix packages Armadillo and Eigen and the GNU Scientific Library as well as RInside which enables you to use R inside C++. These applications are what most of us need to know to really do scientific programming with R and C++. I love this book. -- Robert McCulloch, University of Chicago Booth School of Business
Rcpp is now considered an essential package for anybody doing serious computational research using R. Dirk's book is an excellent companion and takes the reader from a gentle introduction to more advanced applications via numerous examples and efficiency enhancing gems. The book is packed with all you might have ever wanted to know about Rcpp, its cousins (RcppArmadillo, RcppEigen .etc.), modules, package development and sugar. Overall, this book is a must-have on your shelf. -- Sanjog Misra, UCLA Anderson School of Management
The Rcpp package represents a major leap forward for scientific computations with R. With very few lines of C++ code, one has R's data structures readily at hand for further computations in C++. Hence, high-level numerical programming can be made in C++ almost as easily as in R, but often with a substantial speed gain. Dirk is a crucial person in these developments, and his book takes the reader from the first fragile steps on to using the full Rcpp machinery. A very recommended book! -- Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark
"Seamless R and C ++ Integration with Rcpp" provides the first comprehensive introduction to Rcpp. Rcpp has become the most widely-used language extension for R, and is deployed by over one-hundred different CRAN and BioConductor packages. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease. This brings the depth of the R analysis framework together with the power, speed, and efficiency of C++.
Dirk Eddelbuettel has been a contributor to CRAN for over a decade and maintains around twenty packages. He is the Debian/Ubuntu maintainer for R and other quantitative software, edits the CRAN Task Views for Finance and High-Performance Computing, is a co-founder of the annual R/Finance conference, and an editor of the Journal of Statistical Software. He holds a Ph.D. in Mathematical Economics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.
addresses tasks that nearly every SAS programmer needs to do - that is, make
sure that data errors are located and corrected. This book develops and
demonstrates data cleaning programs and macros that you can use as written or
modify for your own special data cleaning needs.
3D Printing with Delta Printers contains detailed descriptions of the innovative delta design including unique hardware, software, and maintenance requirements. The book also covers tips for building your own delta printer as well as examples of common enhancements.
This book will enable you to build, configure, and enhance your delta printer. The topics covered will reveal the often-mysterious nuances of the delta design that will enable your printer to compete with the best of what your 3D printer friends can build.
This book introduces key game production concepts in an artist-friendly way, and rapidly teaches the basic scripting skills you'll need with Unity. It goes on to show how you, as an independent game artist, can create interactive games, ideal in scope for today's casual and mobile markets, while also giving you a firm foundation in game logic and design.
The first part of the book explains the logic involved in game interaction, and soon has you creating game assets through simple examples that you can build upon and gradually expand. In the second part, you'll build the foundations of a point-and-click style first-person adventure game—including reusable state management scripts, dialogue trees for character interaction, load/save functionality, a robust inventory system, and a bonus feature: a dynamically configured maze and mini-map. With the help of the provided 2D and 3D content, you'll learn to evaluate and deal with challenges in bite-sized pieces as the project progresses, gaining valuable problem-solving skills in interactive design. By the end of the book, you will be able to actively use the Unity 3D game engine, having learned the necessary workflows to utilize your own assets. You will also have an assortment of reusable scripts and art assets with which to build future games.
This book is an in-depth guide to the use of pandas for data analysis, for either the seasoned data analysis practitioner or the novice user. It provides a basic introduction to the pandas framework, and takes users through the installation of the library and the IPython interactive environment. Thereafter, you will learn basic as well as advanced features, such as MultiIndexing, modifying data structures, and sampling data, which provide powerful capabilities for data analysis.
· Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques
· Many more diagrams included--now in two color--to provide greater insight through visual presentation
· Matlab code of the most common methods are given at the end of each chapter.
· More Matlab code is available, together with an accompanying manual, via this site
· Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms.
· An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869).Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams included--now in two color--to provide greater insight through visual presentation Matlab code of the most common methods are given at the end of each chapter An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. The companion book is available separately or at a special packaged price (Book ISBN: 9780123744869. Package ISBN: 9780123744913) Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms Solutions manual, powerpoint slides, and additional resources are available to faculty using the text for their course. Register at www.textbooks.elsevier.com and search on "Theodoridis" to access resources for instructor.