Sudeep's Blog

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Install gplots in R > 2.0

2014-03-10 Share on Tumblr

Here is the link: 


Trolling SO

2014-03-07 Share on Tumblr

612.. and counting..

It gets better over time (.. and addictive)

Here: http://stackoverflow.com/users/1391220/sudeep-juvekar

In case you were wondering!

2014-02-04 Share on Tumblr

Thank you and welcome!

Adding Banner Ad to Android App

2014-01-10 Share on Tumblr

Here is how you can add banner ad to Android app.
  • Create an account on AdMob: Provide your bank details etc etc.
  • Create an ad campaign: AdMob makes it extremely easy to create a campaign. After walking through the process you will end up with an ad id of the form: ca-app-pub-XXXXXXXXXXXXXXXX/YYYYYYYYYY
  • Finally, add this code to your MainActivity: public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); Window window = getWindow(); RelativeLayout adsLayout = new RelativeLayout(this); RelativeLayout.LayoutParams lp2 = new RelativeLayout.LayoutParams(RelativeLayout.LayoutParams.MATCH_PARENT, RelativeLayout.LayoutParams.WRAP_CONTENT); adsLayout.setGravity(Gravity.BOTTOM); AdView adView = new AdView(this, AdSize.SMART_BANNER, "ca-app-pub-XXXXXXXXXXXXXXXX/YYYYYYYYYY"); adsLayout.addView(adView); AdRequest newAdReq = new AdRequest(); adView.loadAd(newAdReq); window.addContentView(adsLayout, lp2); }

Happy New Year

2014-01-04 Share on Tumblr

...and happy coding 2014

Processing + eclipse + android

2013-12-19 Share on Tumblr

Here is a step-by-step method to create an processing sketch using Android SDK in Eclipse (instead of processing IDE):


Reactive Programming in Scala

2013-11-24 Share on Tumblr

Here is a set of notes maintained by me and some others on concepts related to event-sriven reactive programming in Scala: https://github.com/sjuvekar/reactive-programming-scala/blob/master/ReactiveCheatSheet.md. 

The notes originated from a Coursera's class with same title: https://class.coursera.org/reactive-001/class

Kaggle's Expedia Learning to Rank Competition

2013-11-06 Share on Tumblr

Kaggle just concluded their Personalized Ranking Competition hosted by Expedia. Here is a link to the competition

This competition is a standout because the dataset provided is considerably bigger than their earlier competitions (about 10M X 30) and the target classes are unbalanced with about 90% of provided data consisting of single class. Any straightforward learning algorithm has many issues:
  • Every new feature increases the size of train data significantly, and soon, with a few number of features, the data becomes too big to fit in main memory
  • A simple cross-validation produces a very high validation score because of unbalanced classes and fails to generalize
Of course, these problems are solvable, and the approach the we tried had few components.
  • Carefully choose train-validation data to keep roughly the same proportion of all classes. More importantly, keep all data-points from same user either completely in train or cross validation set
  • One-vs-all classification approach was found to do better than a multiclass classification. Even there, multiple ordinal classification seemed to perform better. Here is a paper discussing this approach
We used standard gradient boosting for training and obtained an nDCG score od about 0.506. Not a terribly good score, but easily better than benchmark and within top 16% of all contenders. So, no complaints!
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