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CodeIgniter – Open Source PHP framework, used by hundreds of thousands of PHP developers worldwide.
Top 10 PHP Framework: http://www.phpframeworks.com/top-10-php-frameworks/
Here is NetTuts video tutorials about CodeIgniter Framework (all the sample code built on CodeIgniter 1.7)
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For valuable work on creation of sites you need a good comfortable editor necessarily. There are many requiring paid products for this purpose, but we would like to select free of charge very functional and at the same time of simple in the use editor – Codelobster PHP Edition .
The basic model for MapReduce derives from the map and reduce concept in functional languages like Lisp.
In Lisp, a map takes as input a function and a sequence of values and applies the function to each value in the sequence.
A reduce takes as input a sequence of elements and combines all the elements using a binary operation (for example, it can use “+” to sum all the elements in the sequence).
MapReduce, inspired by these concepts, was developed as a method for writing processing algorithms for large amounts of raw data. The amount of data is so large that it can’t be stored on a single machine and must be distributed across many machines in order to be processed in a reasonable time.
In systems with such data distribution, the traditional central processing algorithms are useless as just getting the data to the centralized CPU running the algorithm implies huge network costs and months (!) spent on transferring data from the distributed machines.
Therefore, processing such massive scales of distributed data implies the need for parallel computing allowing us to run the required computation “close” to where the data is located. [Read more...]
I’ve recently answered Predicting missing data values in a database on StackOverflow and thought it deserved a mention on DeveloperZen.
One of the important stages of data mining is preprocessing, where we prepare the data for mining. Real-world data tends to be incomplete, noisy, and inconsistent and an important task when preprocessing the data is to fill in missing values, smooth out noise and correct inconsistencies.
If we specifically look at dealing with missing data, there are several techniques that can be used. Choosing the right technique is a choice that depends on the problem domain – the data’s domain (sales data? CRM data? …) and our goal for the data mining process.
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On the past few weeks I’ve been working on a new venture centered around the iPhone. The process of building our app has been quite an adventure and we’ve experimented with several technologies that were new to us before reaching our current technology stack.
As we’ve finally got our stuff together and made an initial release to a group of testers I thought I’d share some of the technology choices we’ve made and the reasons behind them.
…because technology choices are affected by the team’s technical skillset.
I encountered this post on my weekend reading. 91 Surefire Ways to Become an Event Greater Developer contain a comprehensive guide linking to all sort of blog posts providing insights on improving your skills as a developer.
While the list is very long and sometimes debatable it does have some interesting pointers. If you do nothing else, delve into item #8: Learn Programming by Not Programming referring to the following post by Jeff Atwood.
The topic in question is why some developers outperform their peers regardless of their accumulated experience:
But the dirty little secret of the software development industry is that this is also true even for people who can program: there’s a vast divide between good developers and mediocre developers.
A mediocre developer can program his or her heart out for four years, but that won’t magically transform them into a good developer. And the good developers always seem to have a natural knack for the stuff from the very beginning.
The answer lies in the quotes taken from Bill Gates remarks:
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