Computer Programming

Learn to program with visual examples. Programs increase in complexity as you progress - from drawing a circle to 3D graphics, animations, and simulations. A Graphical Introduction to Programming teaches computer programming with the aid of 100 example programs, each of which int...egrates graphical or sound output. The Processing-language-based examples range from drawing a circle and animating bouncing balls to 3D graphics, audio visualization, and interactive games. Readers learn core programming concepts like conditions, loops, arrays, strings and functions, as well as how to use Processing to draw lines, shapes, and 3D objects. They'll learn key computer graphics concepts like manipulating images, animating text, mapping textures onto objects, and working with video. Advanced examples include sound effects and audio visualization, network communication, 3D geometry and animation, simulations of snow and smoke, predator-prey populations, and interactive games.
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The go-to guide for learning coding from the ground-up Adding some coding know-how to your skills can help launch a new career or bolster an old one. Coding All-in-One For Dummies offers an ideal starting place for learning the languages that make technology go. This edition ge...ts you started with a helpful explanation of how coding works and how it?s applied in the real-world before setting you on a path toward writing code for web building, mobile application development, and data analysis. Add coding to your skillset for your existing career, or begin the exciting transition into life as a professional developer?Dummies makes it easy. Learn coding basics and how to apply them Analyze data and automate routine tasks on the job Get the foundation you need to launch a career as a coder Add HTML, JavaScript, and Python know-how to your resume This book serves up insight on the basics of coding, designed to be easy to follow, even if you?ve never written a line of code in your life. You can do this.
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The fun way to introduce coding with Ruby to kidsIf you don't have the chance to take coding classes at school or in camp-or if you just want to learn on your own-Ruby For Kids gears you up to expand your technology skills and learn this popular programming language.

In just 24 lessons of one hour or less, Sams Teach Yourself Silverlight 4 in 24 Hours will help new and experienced rich application developers gain true mastery over Silverlight 4, and make the most of its powerful new enhancements. In this book's straightforward, step-by-step a...pproach, each lesson builds on everything that's come before, helping you learn all of Silverlight 4's core features from the ground up, and integrate them seamlessly to create more powerful user experiences for a wide variety of devices, including today's hot new Windows Phone 7 cell phones. Friendly, accessible, and conversational, this book covers everything you need to know, from the absolute basics to advanced Silverlight 4 controls and programming techniques. Step-by-step instructions carefully walks you through the most common questions, issues, and tasks...Q and As, Quizzes, and Exercises help you build and test your knowledge... Did You Know? tips offer them insider advice and shortcuts...and Watch Out! alerts help you avoid problems. By the time they're finished with these lessons, you won't just understand Silverlight 4: they'll be comfortable using it in real-world projects.
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We are at crossroads in deep learning. Today, deep learning developers typically utilize one of the top two machine learning frameworks: Tensorflow, developed by Google/Deepmind, and PyTorch, developed by Facebook. In industry, Tensorflow is still more widely adopted. Still, PyTo...rch is rapidly up-and-coming in the research community, where 70%-80% of recently submitted conference research papers utilize PyTorch instead of Tensorflow. A recent 2020 Stack Overflow survey of the most popular frameworks and libraries reported that PyTorch was selected by an est 30% of respondents vs. 70% for Tensorflow, with PyTorch nearly doubling in popularity over the last two years. In the next couple of years, as these machine learning frameworks become equal in popularity, a book must well verse developers in both so they can choose the right methodology to help solve their deep learning problems. The problem is that most deep learning books published today focus on just one of the machine learning frameworks.Python Deep Learningwould identify both frameworks' pros and cons and then teach deep learning concepts utilizing practical examples from the framework best suited for particular problems. This book also features the APIs and libraries integrated with the respective framework, Keras for Tensorflow and fastai for PyTorch, that make application development and deployment even more straightforward. What this Books Covers: Introduction and overview of deep learning concepts Description of the two machine learning frameworks: Tensorflow and PyTorch, as well as successful examples of their usage Detail the pros and cons of each machine learning framework Overview of the supportive libraries and APIs (including Keras and fastai) for each of the frameworks that make application development simpler Chapter-by-chapter review of the top neural network topologies (CNN, RNN, LSTM, MLP, and several newer variants) Interesting code examples of practical applications of the differe
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