Camelot

Cathy O’Neil’s book Weapons of Math Destruction explores the dark side of Big Data. In particular, it explores a number of case studies that highlight the damage that can be done through the misuse or outright abuse of statistical models, with an emphasis on the socioeconomic impact. [Read More]

I recently read Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz. It was an interesting read that focused on the raw power of Big Data and the insights that can be achieved by looking at the online... [Read More]

The Bias-Variance Tradeoff is a fairly prevalent problem in machine learning and predictive modeling. At a high level, it can be summarized in a brief story called “Goldilocks and the Three Data Scientists”: “This model is too simple.” “This model is too complex.” “This model is JUST right.” [Read More]

See the code on GitHub!! [Read More]

I created this blog while I was studying in the Metis data science program. While they were very helpful in setting up the foundations for my site, there were a lot of features and opportunities I had to discover on my own. I want to quickly mention of the low-hanging... [Read More]