By Brad Green, Shyam Seshadri
Guided through engineers who labored on AngularJS at Google, you’ll stroll in the course of the framework’s key positive aspects, after which construct a operating AngularJS app—from structure to trying out, compiling, and debugging. You’ll learn the way AngularJS is helping decrease the complexity of your internet app.
* Dive deep into Angular’s development blocks and find out how they interact
* achieve greatest flexibility by way of setting apart good judgment, facts, and presentation tasks with MVC
* gather your complete app within the browser, utilizing client-side templates
* Use AngularJS directives to increase HTML with declarative syntax
* converse with the server and enforce basic caching with the $http carrier
* Use dependency injection to enhance refactoring, testability, and a number of atmosphere layout
* Get code samples for universal difficulties you face in such a lot internet apps
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Extra info for AngularJS
But what if all symbols aren't equally probable? To compute the entropy, you need to weigh the information of each symbol by its probability of occurring. This formulation, known as Shannon's Entropy (named after Claude Shannon), is shown in Figure 4-2. Figure 4-2. Equation 4-2 Entropy (H) is the negative sum over all the symbols (n) of the probability of a symbol (pi) multiplied by the log base 2 of the probability of a symbol (log2pi). Let's work through a couple of examples to make this clear.
You can also think of information as a degree of surprise. " The child is very predictable, and you are pretty certain of the answer the next time you ask a question. There's no surprise, no information, and no communication. If another child answers "yes" or "no" to some questions, you can communicate a little, but you can communicate more if her vocabulary was greater. " Qualitatively, you expect more information to be conveyed by a greater vocabulary and from surprising answers. Thus, the information or surprise of an answer is inversely proportional to its probability.
Prokaryotes often have a single circular chromosome, and eukaryotes usually have multiple linear chromosomes. People are sometimes surprised to find that genome size and chromosome number aren't reflected in organismal complexity. For example, the single-celled Amoeba dubia has a genome that is about 200 times larger than the human genome. Although dogs and cats have very similar genome sizes, dogs have twice as many chromosomes. One rule to keep in mind when thinking about genomic organization is that genomes of viruses and prokaryotic organisms generally contain little noncoding sequence, whereas the genomes of more complex organisms usually contain a much higher percentage of noncoding sequence.