Long recognized as very applied and practical, Eggen and Kauchak's Educational Psychology: Windows on Classrooms, seventh edition is now even more applied and concise, giving students exactly what they need to know in the course. The author's hallmark cases remain, in both written and videotape format, to introduce real-world applications in a way that no other text can. Along with expanded applications to diversity (urban, suburban, and rural areas), technology, and a new pedagogical system that completely restructures how information is delivered in the book and will help students really understand what they should be getting out of every single chapter. The text now comes with two new DVDs of video material and an access code for the new Teacher Prep Website that will be automatically shrinkwrapped with all new copies of the text. Educational Psychology: Windows on Classrooms once again truly fulfills the promise of its title, giving students a window on the classrooms in which they will someday teach.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    It could forever change how you experience and interact with your physical surroundings, open your eyes to the perversity of bad design and the desirability of good design, and raise your expectations about how things should be designed.B & W photographs and illustrations throughout.

    This is the currently used textbook for "Probabilistic Systems Analysis," an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains, a number of more advanced topics, from which an instructor can choose to match the goals of a particular course. These topics include transforms, sums of random variables, least squares estimation, the bivariate normal distribution, and a fairly detailed introduction to Bernoulli, Poisson, and Markov processes. The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis has been just intuitively explained in the text, but is developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems. The book has been widely adopted for classroom use in introductory probability courses within the USA and abroad.

    Ware's updated review of empirical research and interface design examples will do much to accelerate innovation and adoption of information visualization." —Ben Shneiderman, University of Maryland"Colin Ware is the perfect person to write this book, with a long history of prominent contributions to the visual interaction with machines and to information visualization directly. It goes a long way towards joining science to the practical design of information visualization systems." —from the foreword by Stuart Card, PARCMost designers know that yellow text presented against a blue background reads clearly and easily, but how many can explain why, and what really are the best ways to help others and ourselves clearly see key patterns in a bunch of data? When we use software, access a web site, or view graphics, our understanding is greatly enhanced or impeded by the way information is presented. By explaining in detail how we think visually, this book provides guidance on how to construct effective interactive information displays.This book combines a strictly scientific approach to human perception with a practical concern for the rules governing the effective visual presentation of information. Surveying the research of leading psychologists and neurophysiologists, author Colin Ware isolates key principles at work in vision and perception, and from them derives specific and effective visualization techniques suitable for a wide range of scenarios. Information Visualization offers practical guidelines that can be applied by anyone, and covers all facets of visual perception: color, organization, space perception, motion, and texture.* Major revision of this classic work, with a new chapter on visual thinking, new sections on face perception and flow visualization, an appendix on how to evaluate visualizations,and a greatly expanded chapter on color and color sequences. *New to this edition is the full-color treatment throughout, to better display over 400 illustrations.*From a leading researcher in the field of human perception who has brought together, in a single resource, all current scientific insight into the question of data visualization.

    The Text Was Designed To Familiarize Students With The Foundations And Principles Of Computer Science And To Strengthen The Students' Ability To Carry Out Formal And Rigorous Mathematical Arguments. In The New Fourth Edition, Author Peter Linz Has Offered A Straightforward, Uncomplicated Treatment Of Formal Languages And Automata And Avoids Excessive Mathematical Detail So That Students May Focus On And Understand The Underlying Principles. In An Effort To Further The Accessibility And Comprehension Of The Text, The Author Has Added New Illustrative Examples Throughout.

    From the laws of libel and privacy to the regulation of advertising and telecommunications, Mass Media Law examines timely issues that are shaping the United States' legal system and the future of media content.

    As the words "at work" suggest, Peter Seibel focuses on how his interviewees tackle the day–to–day work of programming, while revealing much more, like how they became great programmers, how they recognize programming talent in others, and what kinds of problems they find most interesting. Hundreds of people have suggested names of programmers to interview on the Coders at Work web site: http://www.codersatwork.com. The complete list was 284 names. Having digested everyone’s feedback, we selected 16 folks who’ve been kind enough to agree to be interviewed:- Frances Allen: Pioneer in optimizing compilers, first woman to win the Turing Award (2006) and first female IBM fellow- Joe Armstrong: Inventor of Erlang- Joshua Bloch: Author of the Java collections framework, now at Google- Bernie Cosell: One of the main software guys behind the original ARPANET IMPs and a master debugger- Douglas Crockford: JSON founder, JavaScript architect at Yahoo!- L. Peter Deutsch: Author of Ghostscript, implementer of Smalltalk-80 at Xerox PARC and Lisp 1.5 on PDP-1- Brendan Eich: Inventor of JavaScript, CTO of the Mozilla Corporation - Brad Fitzpatrick: Writer of LiveJournal, OpenID, memcached, and Perlbal - Dan Ingalls: Smalltalk implementor and designer- Simon Peyton Jones: Coinventor of Haskell and lead designer of Glasgow Haskell Compiler- Donald Knuth: Author of The Art of Computer Programming and creator of TeX- Peter Norvig: Director of Research at Google and author of the standard text on AI- Guy Steele: Coinventor of Scheme and part of the Common Lisp Gang of Five, currently working on Fortress- Ken Thompson: Inventor of UNIX- Jamie Zawinski: Author of XEmacs and early Netscape/Mozilla hackerWhat you’ll learn:How the best programmers in the world do their jobWho is this book for?Programmers interested in the point of view of leaders in the field. Programmers looking for approaches that work for some of these outstanding programmers.

    The R language is recognised as one of the most powerful and flexible statistical software packages, and it enables the user to apply many statistical techniques that would be impossible without such software to help implement such large data sets.

    You thought TDD was for someone else, but it's not! It's for you, the embedded C programmer. TDD helps you prevent defects and build software with a long useful life. This is the first book to teach the hows and whys of TDD for C programmers. TDD is a modern programming practice C developers need to know. It's a different way to program---unit tests are written in a tight feedback loop with the production code, assuring your code does what you think. You get valuable feedback every few minutes. You find mistakes before they become bugs. You get early warning of design problems. You get immediate notification of side effect defects. You get to spend more time adding valuable features to your product. James is one of the few experts in applying TDD to embedded C. With his 1.5 decades of training, coaching, and practicing TDD in C, C++, Java, and C# he will lead you from being a novice in TDD to using the techniques that few have mastered. This book is full of code written for embedded C programmers. You don't just see the end product, you see code and tests evolve. James leads you through the thought process and decisions made each step of the way. You'll learn techniques for test-driving code right next to the hardware, and you'll learn design principles and how to apply them to C to keep your code clean and flexible. To run the examples in this book, you will need a C/C++ development environment on your machine, and the GNU GCC tool chain or Microsoft Visual Studio for C++ (some project conversion may be needed).

    This tenth edition reflects the needs of students and assures the development of practical and marketable skills. It helps them learn: how to query data and obtain results, by presenting the SQL Select. It provides a framework to help students learn this material.

    Concepts and techniques are presented in a clear and concise style, giving readers the opportunity to master key topics.

    Written by two internationally acclaimed experts on requirements, this text provides software engineers with the insights, techniques and templates to discover exactly what their customers desire for their systems.

    It covers such areas as biotechnology and biomedical engineering.

    It explores the critical concepts while also examining why they are relevant. The core content is presented within the framework of predicting products, proposing mechanisms, and solving synthesis problems. Readers will fine-tune the key skills involved in solving those types of problems with the help of interactive, step-by-step instructions and problems.