Latest posts

Analyzing the evolution of Linkin Park's music over the years Part 2 : Moods

In the previous blog post, we saw how Linkin Park's musical style changed over the years, by looking at the mean and variation of audio features of their songs. In particular, we looked at 4 audio features - duration, energy, loudness, and valence. In this post, we'll try to encapsulate 2 of those features (energy and valence

Analyzing the evolution of Linkin Park's music over the years

Like a vast number of urban teenagers, Linkin Park was one of my favorite rock bands during my high school years. The moods and emotions that their music captures resonate with all kinds of different age groups, so you may have discovered their music later on in your life.

Linkin Park's music has progressed a lot of over the years, from the radio-friendly nu-metal days of Hybrid Theory

Sentiment Analysis on lyrics of popular music artists

In this post, we are going to analyze lyrics of some of the popular artists nowadays. Music and analysis are two of my favourite things, and it was kind of obvious to combine both of them. Since I've been known to delve into analysis paralysis while making decisions, I chose to ask people on my facebook friends list about which artists they were currently listening to, instead of coming up with my own list (My propensity to listen to obscure artists doesn't help).

Football subreddit word clouds - Visualizing transfer window madness

Reddit is one of my favourite discussion websites. It is a forum where people can post links or text posts which are downvoted and upvoted by users. "Subreddits" are communities based on a certain topic - like business, news, sports. Being a big football fan, I frequently visit the football-related subreddits. If you've been following European football at all, you'll know that even though the transfer window is not yet over, the past month or so has been crazy in terms of transfer news.

Playing around with the breast cancer dataset

The Breast Cancer Dataset is a dataset of features computed from breast mass of candidate patients. Each instance of features corresponds to a malignant or benign tumour. The motivation behind studying this dataset is the develop an algorithm, which would be able to predict whether a patient has a malignant or benign tumour, based on the features computed from her breast mass. I decided to use this dataset for my first blog post on machine learning, since its a very straightforward dataset with no missing values and all variables being real valued (no categorical variables).