A!

http://webdesign.tutsplus.com/tutorials/build-a-dynamic-dashboard-with-chartjs--webdesign-14363 http://keen.github.io/dashboards/examples/ http://usebootstrap.com/theme/sb-admin

import java.io.BufferedReader; import java.io.FileNotFoundException; import java.io.FileReader; import java.io.IOException; public class ReadCVS {   public static void main(String[] args) { ReadCVS obj = new ReadCVS(); obj.run();   }   public void run() { String csvFile = "DailyData.csv"; BufferedReader br = null; String line = ""; String cvsSplitBy = ","; try { br = new BufferedReader(new FileReader(csvFile)); while ((line = br.readLine()) != null) {        // use comma as separator String[] splits = line.split(cvsSplitBy); System.out.println(splits[4]                                   +splits[5]); } } catch (FileNotFoundException e) { e.printStackTrace(); } catch (IOException e) { e.printStackTrace(); } finally { if (br != null) { try { br.close(); } catch (IOException e) { ...

Hadoop Hello World: The Word Count Code: The word count code is the simplest program to get you started with Map Reduce Framework. The task that a wordcount program performs is as follows: Given several text files find a count of number of times each word appears in the entire set It primarily consists of 3 parts: Driver    : Driver portion of the code contains the configuration details for the Hadoop Job. For example the input path, the output path, number of reducers , mapper class name, reducer class name etc Mapper  : Role of mapper in word count is to emit <word, 1>  for each word appearing in the document. Reducer : Role of Reducer in word count is to sum the list of 1's prepared by shuffle and sort phase <word, [1,1,1,1,1,1]>  and emit <word, 6> It's easier to create an eclipse java project and add relevant hadoop jar files for the code below.  package com.kush; import java.io.IOException; import java.uti...

Monkey to a Man/Women

I came across this interesting plot showing different algorithms, their inventors and their usage trend. Clearly, Neural Networks and Deep Belief Networks have revived and have a way to go. There is an interesting discussion on Quora, which users of these algorithms may be interested in: http://www.quora.com/Will-deep-learning-make-other-Machine-Learning-algorithms-obsolete

I think every AI system desinger should go through these before starting to work on a project. Here i found a good article on the above two cases: http://www.heritage.org/research/reports/2009/03/three-mile-island-and-chernobyl-what-went-wrong-and-why-todays-reactors-are-safe

Finally started my internship at Honeywell. I have to build a Adaptive Neuro Fuzzy Inference Engine as a part of the project. The name seems really scary but i think i'll get lots of things to learn under my highly experienced mentors.