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PHP and MySQL Web Development

Master today’s best practices for succeeding with PHP 5.6 and MySQL 5.6 web database development! Long acknowledged as the clearest, most practical, and most down-to-earth guide to PHP/MySQL web development, the brand-new Fifth Edition of PHP and MySQL Web Development fully reflects the latest versions of PHP and MySQL. Maintaining the approach that has made this book so successful through, Luke Welling and Laura Thomson add extensive new coverage of security, cloud and mobile development, and using the PEAR repository’s massive resources. Part I offers a crash course in using PHP, including data storage/retrieval, arrays, strings, regular expressions, code reuse, objects, and error/exception handling. Next, walk through designing, creating, accessing, and programming MySQL databases. Part III turns to e-commerce, adding extensive new coverage of web security, plus up-to-the-minute discussions of authentication and secure transactions. A full section of advanced PHP techniques addresses everything from networking and filesystem interaction to image generation and session control. The authors conclude with primers on real-world development and debugging, followed by ten start-to-finish case studies, from authentication to content management, personalized PDFs to web services and Web 2.0 apps.

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R for Everyone

$55.60

Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write user-defined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and t-tests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via K-means and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available. Normal 0 false false false EN-US X-NONE X-NONE

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