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The concept of "unobtrusiveness" in relation to client-side JavaScript was coined in 2002 by Stuart Langridge [7] in the article "Unobtrusive DHTML, and the power of unordered lists". [8] In the article Langridge argued for a way to keep all JavaScript code, including event handlers, outside of the HTML when using dynamic HTML (DHTML). [7]
W3Schools is a freemium educational website for learning coding online. [1] [2] Initially released in 1998, it derives its name from the World Wide Web but is not affiliated with the W3 Consortium. [3] [4] [unreliable source] W3Schools offers courses covering many aspects of web development. [5] W3Schools also publishes free HTML templates.
A PHP Ajax framework is able to deal with database, search data, and build pages or parts of page and publish the page or return data to the XMLHttpRequest object. Quicknet is an Ajax framework that provides secure data transmission, uses PHP on the server side; Sajax PHP framework with a lot of functions, easy to integrate functions yourself
Because of its expressive power and (relative) ease of reading, many other utilities and programming languages have adopted syntax similar to Perl's—for example, Java, JavaScript, Julia, Python, Ruby, Qt, Microsoft's .NET Framework, and XML Schema. Some languages and tools such as Boost and PHP support multiple regex flavors. Perl-derivative ...
Correlated subqueries may appear elsewhere besides the WHERE clause; for example, this query uses a correlated subquery in the SELECT clause to print the entire list of employees alongside the average salary for each employee's department.
In database design, a lossless join decomposition is a decomposition of a relation into relations , such that a natural join of the two smaller relations yields back the original relation.
The PHP serialization format is the serialization format used by the PHP programming language. The format can serialize PHP's primitive and compound types, ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]