GPU Accelerated Matrix Factorization for Recommender Systems
Matrix Factorization (MF) is a popular algorithm used to power many recommender systems. Efficient and scalable MF algorithms are essential in order to train...
Doruk's Blog
a collection of posts about Data Science and other stuff
Running Jupyter Notebook on NYU HPC in 3 Clicks
I’ve been lately getting a lot of question about my setup for NYU’s High Performance Computing cluster and how it can be made more convenient to use. In this...
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...
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...
Data Science workflow using Ubuntu Subsystem on Windows
Microsoft’s latest push for bringing developers to Windows comes in the form of embracing Linux as part of their system. Windows Subsystem for Linux, also kn...
Adventures with RapidMiner
For our Big Data Science course @ NYU, me, Nick, and Amit are building a Book Recommender System, specifically for using with GoodReads. Although the exact d...