Category Archives for Technical

Deep Learning for layman

Prologue : Today Deep learning is a buzz word like how data science and machine learning was yesterday. And it is no surprise that you would blow up with too information with too complicated terminologies and glossaries when you try to understand Deep learning with the materials available on online. This blog is written with […]

ROC-Receiver Operating Characteristic

Two days ago, myself and the person whom I had no idea had a healthy conversion on classification models, interesting we were discussing about potential techniques and approaches that should be followed to select an optimal classification model for better results. At some point I suggested him ROC curves for the same reason. Receiver operating […]

Distance Measures – What is Similarity, Dissimilarity and Correlation

The term distance measure has got wide variety of definitions among the math and data mining practitioners. As a result those terms, concepts and their usage went way beyond the head for beginner who try started understand them for first time. And today I write this post to give more simplified and very intuitive definitions […]

What is the difference between Artificial Intelligence, Machine Learning, Statistics, and Data Mining

Few day ago before I saw an interesting question on that got my attention for a while. After spending few minutes of readings and analyzing all answers on stack I felt writing my thoughts assuming what I would have answered if I really had too. What is the difference between Artificial Intelligence, Machine Learning, Statistics, […]

Low-rank matrix approximation with SVD – Part 2

In part-1 we have revising the internal workings of singular value decomposition.  Here in part 2 lets see the practical usage of SVD. All source code and corpus used in this excise can be found on my github-Account. Singular value decomposition (SVD) has a wide range of usage in the statistical study however it is more […]

Revising singular value decomposition – Part 1

Few days before I had small issues in understanding the internal workings of SVD. The Worst part is I have already done few projects which has SVD as a major module. This is the time I decided to revisit and recall every thing I need to know about decomposition techniques (Well, this is also he […]

Dynamic scoping rules

R uses Lexical scoping rules, unlike R many other languages use Dynamic scoping for assigning values to their free variables. Its good to know what is Dynamic scoping and how it is different from lexical scoping. So followed by my previous post on lexical scoping I took privilege to write a short post on dynamic […]

Lexical scoping rule in R

I am getting familiar in R and on this go I came across the concepts of lexical scoping rules in R functions. I had slightly difficult time in understanding the concepts as I came form a language that has dynamic scoping as a background. And below post (Lexical scoping rule in R) is a short […]

Word Cloud on Thirukural

Building word cloud isn’t that much scary until I know I could do this myself with some statistical packages provided in R. For this expedition I decided to build word cloud on Thirukural. Thirukural is one the finest master pieces in the Tamil literature works which is believed to written during the Tamil sangam period. […]

Mining Associations with Apriori using R – Part 2

Prologue: I have been working and practicing various skills and algorithms as a progress to show on my road-map to become as a matured data scientist. As a part of this expedition I have decided to document all those stuffs I am going through. So whatever you read under this column will be either a summary […]