Hierarchical Clustering and its Applications
Clustering is one of the most well known techniques in Data Science. From customer segmentation to outlier detection, it has a broad range of uses, and diffe...
Doruk's Blog
a collection of posts about Machine Learning and other stuff
Recommender Systems: From Filter Bubble to Serendipity
Recommender systems power a lot of our day to day interactions with the content we see on the internet. With over 2.5 quintillion bytes of data created each ...
Representation Learning through Matrix Factorization
Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) has been around for a while, and have been successfully utilized for learning inter...
Why you should use PCA before Decision Trees
Dimensionality Reduction techniques have been consistently useful in Data Science and Machine Learning. It can reduce training times, allow you to remove fea...
Introducing Books2Rec
I am proud to announce Books2Rec, the book recommendation system I have been working for the last couple of months, is live. Using your Goodreads profile, Bo...
Representation Learning: An Introduction
Representation Learning is a relatively new term that encompasses many different methods of extracting some form of useful representation of the data, based ...