## Similar Ebooks

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.

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 detailsLogically Fallacious is one of the most comprehensive collections of logical fallacies with all original examples and easy to understand descriptions, perfect for educators, debaters, or anyone who wants to improve his or her reasoning skills.

"Expose an irrational belief, keep a person rational for a day. Expose irrational thinking, keep a person rational for a lifetime." - Bo Bennett

Why do some games become boring quickly, while others remain fun for years? How do games serve as fundamental and powerful learning tools? Whether you’re a game developer, dedicated gamer, or curious observer, this illustrated, fully updated edition helps you understand what drives this major cultural force, and inspires you to take it further.

You’ll discover that:

Games play into our innate ability to seek patterns and solve puzzlesMost successful games are built upon the same elementsSlightly more females than males now play gamesMany games still teach primitive survival skillsFictional dressing for modern games is more developed than the conceptual elementsTruly creative designers seldom use other games for inspirationGames are beginning to evolve beyond their prehistoric originsThe antidote to fuzzy thinking, with furry animals!

Have you read (or stumbled into) one too many irrational online debates? Ali Almossawi certainly had, so he wrote An Illustrated Book of Bad Arguments! This handy guide is here to bring the internet age a much-needed dose of old-school logic (really old-school, a la Aristotle).

Here are cogent explanations of the straw man fallacy, the slippery slope argument, the ad hominem attack, and other common attempts at reasoning that actually fall short—plus a beautifully drawn menagerie of animals who (adorably) commit every logical faux pas. Rabbit thinks a strange light in the sky must be a UFO because no one can prove otherwise (the appeal to ignorance). And Lion doesn’t believe that gas emissions harm the planet because, if that were true, he wouldn’t like the result (the argument from consequences).

Once you learn to recognize these abuses of reason, they start to crop up everywhere from congressional debate to YouTube comments—which makes this geek-chic book a must for anyone in the habit of holding opinions.

Logic For Dummies tracks an introductory logic course at the college level. Concrete, real-world examples help you understand each concept you encounter, while fully worked out proofs and fun logic problems encourage you students to apply what you’ve learned.

Volume XIII contains 14 papers which introduce a number of new advances in both the foundations and the applications of rough sets. These are mathematical structures of generalized rough sets in infinite universes, approximations of arbitrary binary relations, and attribute reduction in decision-theoretic rough sets. Methodological advances introduce rough set-based and hybrid methodologies for learning theory, attribution reduction, decision analysis, risk assessment, and data mining tasks such as classification and clustering. In addition, this volume contains regular articles on mining temporal software metrics data, C-GAME discretization method, perceptual tolerance intersection as an example of a near set operation and compression of spatial data with quadtree structures.

Volume XX in the series is a continuation of a number of research streams that have grown out of the seminal work of Zdzislaw Pawlak during the first decade of the 21st century.

Rather than focus on design, CSS Secrets shows you how to solve problems with code. You'll learn how to apply Lea's analytical approach to practically every CSS problem you face to attain DRY, maintainable, flexible, lightweight, and standards-compliant results.

Inspired by her popular talks at over 60 international web development conferences, Lea Verou provides a wealth of information for topics including:

Backgrounds and BordersShapesVisual EffectsTypographyUser ExperienceStructure and LayoutTransitions and AnimationsContents include: Sets and Relations — Cantor's concept of a set, etc.

Natural Number Sequence — Zorn's Lemma, etc.

Extension of Natural Numbers to Real Numbers

Logic — the Statement and Predicate Calculus, etc.

Informal Axiomatic Mathematics

Boolean AlgebraInformal Axiomatic Set TheorySeveral Algebraic Theories — Rings, Integral Domains, Fields, etc.

First-Order Theories — Metamathematics, etc.

Symbolic logic does not figure significantly until the final chapter. The main theme of the book is mathematics as a system seen through the elaboration of real numbers; set theory and logic are seen s efficient tools in constructing axioms necessary to the system.

Mathematics students at the undergraduate level, and those who seek a rigorous but not unnecessarily technical introduction to mathematical concepts, will welcome the return to print of this most lucid work.

"Professor Stoll . . . has given us one of the best introductory texts we have seen." — Cosmos.

"In the reviewer's opinion, this is an excellent book, and in addition to its use as a textbook (it contains a wealth of exercises and examples) can be recommended to all who wish an introduction to mathematical logic less technical than standard treatises (to which it can also serve as preliminary reading)." — Mathematical Reviews.

Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.

Develop a naïve Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a “whom to follow” recommendation system from Twitter dataThis innovative, comprehensive book examines the user-centered design process from the perspective of a designer. With rich imagery,Interactive Designintroduces the different UX players, outlines the user-centered design process from user research to user testing, and explains through various examples how user-centered design has been successfully integrated into the design process of a variety of design studios worldwide.

Volume XIX in the series focuses on the current trends and advances in both the foundations and practical applications of rough sets. It contains 7 extended and revised papers originally presented at the Workshop on Rough Set Applications, RSA 2012, held in Wroclaw, Poland, in September 2012. In addition, the book features 3 contributions in the category of short surveys and monographs on the topic.

Inspired by Lean and Agile development theories, Lean UX lets you focus on the actual experience being designed, rather than deliverables. This book shows you how to collaborate closely with other members of your Agile product team, and gather feedback early and often. You’ll learn how to drive the design in short, iterative cycles to assess what works best for the business and the user. Lean UX shows you how to make this change—for the better.

Frame a vision of the problem you’re solving and focus your team on the right outcomesBring the designers’ toolkit to the rest of your product teamShare your insights with your team much earlier in the processCreate Minimum Viable Products to determine which ideas are validIncorporate the voice of the customer throughout the project cycleMake your team more productive: combine Lean UX with Agile’s Scrum frameworkUnderstand the organizational shifts necessary to integrate Lean UXWith 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 OpenCVThis 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 DetailGoogle'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 approachGet 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.

This book helps to improve your calculation skill and provide magical techniques that makes easier your mathematical problems and solve in just few moments. The book of Short Tricks of Math covers large number of example with short technique solutions for the purpose of quick practice for basics of Math.

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Combining stories of great writers and philosophers with quotations and riddles, this completely original text for first courses in mathematical logic examines problems related to proofs, propositional logic and first-order logic, undecidability, and other topics. 2013 edition.

Volume XVIII includes extensions of papers from the Joint Rough Set Symposium (JRS 2012), which was held in Chengdu, China, in August 2012. The seven papers that constitute this volume deal with topics such as: rough fuzzy sets, intuitionistic fuzzy sets, multi-granulation rough sets, decision-theoretic rough sets, three-way decisions and their applications in attribute reduction, feature selection, overlapping clustering, data mining, cost-sensitive learning, face recognition, and spam filtering.

No prior experience in UX or design is necessary to get started. If you’re an entrepreneur or an innovator, this book puts you right to work with proven tips and tools for researching, identifying, and designing an intuitive, easy-to-use product.

Determine whether people will buy your product before you build itListen to your customers throughout the product’s lifecycleUnderstand why you should design a test before you design a productGet nine tools that are critical to designing your productDiscern the difference between necessary features and nice-to-havesLearn how a Minimum Viable Product affects your UX decisionsUse A/B testing in conjunction with good UX practicesSpeed up your product development process without sacrificing qualityForget dry, technical material. This book—based on the wildly popular UX Crash Course from Joel Marsh’s blog The Hipper Element—is laced with the author's snarky brand of humor, and teaches UX in a simple, practical way. Becoming a professional doesn’t have to be boring.

Follow the real-life UX process from start-to-finish and apply the skills as you learn, or refresh your memory before the next meeting. UX for Beginners is perfect for non-designers who want to become designers, managers who teach UX, and programmers, salespeople, or marketers who want to learn more.

Start from scratch: the fundamentals of UXResearch the weird and wonderful things users doThe process and science of making anything user-friendlyUse size, color, and layout to help and influence usersPlan and create wireframesMake your designs feel engaging and persuasiveMeasure how your design works in the real worldFind out what a UX designer does all dayLearning 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.

This book is ideal for data scientists who are familiar with C++ or Python and perform machine learning activities on a day-to-day basis. Intermediate and advanced machine learning implementers who need a quick guide they can easily navigate will find it useful.

What You Will LearnBecome familiar with the basics of the TensorFlow machine learning libraryGet to know Linear Regression techniques with TensorFlowLearn SVMs with hands-on recipesImplement neural networks and improve predictionsApply NLP and sentiment analysis to your dataMaster CNN and RNN through practical recipesTake TensorFlow into productionIn DetailTensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You'll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google's machine learning library TensorFlow.

This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP.

Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.

Style and approachThis book takes a recipe-based approach where every topic is explicated with the help of a real-world example.

"This book is a very specialized but broadly useful introduction to set theory. It is aimed at 'the beginning student of advanced mathematics' … who wants to understand the set-theoretic underpinnings of the mathematics he already knows or will learn soon. It is also useful to the professional mathematician who knew these underpinnings at one time but has now forgotten exactly how they go. … A good reference for how set theory is used in other parts of mathematics." — Allen Stenger, The Mathematical Association of America, September 2011.

With this book, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. Through full engagement with the sort of real-world problems data-wranglers face, you'll learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, market analysis, and clustering.

The implementations of CV methods in Matlab and Mathematica, classification of chapter problems with the symbols (easily solved) and (challenging) and its extensive glossary of key words, examples and connections with the fabric of CV make the book an invaluable resource for advanced undergraduate and first year graduate students in Engineering, Computer Science or Applied Mathematics.

It offers insights into the design of CV experiments, inclusion of image processing methods in CV projects, as well as the reconstruction and interpretation of recorded natural scenes.

Whether you’re an entrepreneur, UX/UI designer, product manager, or part of an intrapreneurial team, this book teaches simple-to-advanced strategies that you can use in your work right away. Along with business cases, historical context, and real-world examples throughout, you’ll also gain different perspectives on the subject through interviews with top strategists.

Define and validate your target users through provisional personas and customer discovery techniquesConduct competitive research and analysis to explore a crowded marketplace or an opportunity to create unique valueFocus your team on the primary utility and business model of your product by running structured experiments using prototypesDevise UX funnels that increase customer engagement by mapping desired user actions to meaningful metricsThis comprehensive text/reference is the first of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, with a specific focus on practical tools, applications, and open avenues for further research (the other two volumes review issues of Security and Privacy, and Mining and Visualization in CSNs).

Topics and features: includes a thorough introduction to this exciting and blossoming field; presents the latest advances in CSNs, and illustrates how organizations can gain a competitive advantage by applying these ideas in real-world scenarios; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, the representation and analysis of social networks, and the use of semantic networks in knowledge discovery and visualization; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.

This authoritative work is a useful resource for researchers and developers involved in social network research and related issues. Postgraduate and senior undergraduate students will also find this a valuable reference for courses on CSNs.

Because these new developments in logical thought tended to perfect and sharpen the deductive method, an indispensable tool in many fields for deriving conclusions from accepted assumptions, the author decided to widen the scope of the work. In subsequent editions he revised the book to make it also a text on which to base an elementary college course in logic and the methodology of deductive sciences. It is this revised edition that is reprinted here.

Part One deals with elements of logic and the deductive method, including the use of variables, sentential calculus, theory of identity, theory of classes, theory of relations and the deductive method. The Second Part covers applications of logic and methodology in constructing mathematical theories, including laws of order for numbers, laws of addition and subtraction, methodological considerations on the constructed theory, foundations of arithmetic of real numbers, and more. The author has provided numerous exercises to help students assimilate the material, which not only provides a stimulating and thought-provoking introduction to the fundamentals of logical thought, but is the perfect adjunct to courses in logic and the foundation of mathematics.

Such an approach endows the present treatise with a unique character. Due to this uniqueness in the treatment of the subject, the book will be useful to researchers, graduate and pre-graduate students from various disciplines, such as computer science, mathematics and philosophy. It features an impressive number of examples supported by about 40 tables and 230 figures. The comprehensive index of concepts turns the book into a sort of encyclopaedia for researchers from a number of fields.

'A Geometry of Approximation' links many areas of academic pursuit without losing track of its focal point, Rough Sets.

The two-part selection of puzzles and paradoxes begins with examinations of the nature of infinity and some curious systems related to Gödel's theorem. The first three chapters of Part II contain generalized Gödel theorems. Symbolic logic is deferred until the last three chapters, which give explanations and examples of first-order arithmetic, Peano arithmetic, and a complete proof of Gödel's celebrated result involving statements that cannot be proved or disproved. The book also includes a lively look at decision theory, better known as recursion theory, which plays a vital role in computer science.

This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches.

We are proud to offer the readers this book.

“For years now, I’ve been running around preaching to anyone who’ll listen that UX is something that everybody (not just UX people) needs to be doing. Dave has done an excellent job of explaining what developers need to know about UX, in a complete but compact, easy-to-absorb, and implementable form. Developers, come and get it!”

—Steve Krug, author of Don’t Make Me Think! A Common Sense Approach to Web Usability

Master User Experience and Interaction Design from the Developer’s Perspective

For modern developers, UX expertise is indispensable: Without outstanding user experience, your software will fail. Now, David Platt has written the first and only comprehensive developer’s guide to achieving a world-class user experience.

Quality user experience isn’t hard, but it does require developers to think in new ways. The Joy of UX shows you how, with plenty of concrete examples. Firmly grounded in reality, this guide will help you optimize usability and engagement while also coping with difficult technical, schedule, and budget constraints.

Platt’s technology-agnostic approach illuminates all the principles, techniques, and best practices you need to build great user experiences for the web, mobile devices, and desktop environments. He covers the entire process, from user personas and stories through wireframes, layouts, and execution. He also addresses key issues—such as telemetry and security—that many other UX guides ignore. You’ll find all the resources and artifacts you need: complete case studies, sample design documents, testing plans, and more.

This guide shows you how to

Recognize and avoid pitfalls that lead to poor user experiences Learn the crucial difference between design and mere decoration Put yourself in your users’ shoes—understand what they want (and where, when, and why) Quickly sketch and prototype user interfaces for easy refinement Test your sketches on real users or appropriate surrogates Integrate telemetry to capture the best possible usage information Use analytics to accurately interpret the data you’ve captured Solve unique experience problems presented by mobile environments Secure your app without compromising usability any more than necessary “Polish” your UX to eliminate user effort everywhere you can

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