Data Science

A New Way to “See” Reviews with Word Clouds

Information overload is a very real phenomena as digital and information technology progresses. While companies relish in harvesting personal data for increasingly effective advertising, the individual can rarely make use of the same amount of information. Consider the simple act of choosing a restaurant. Going on Yelp or any review site would be a good… Continue reading A New Way to “See” Reviews with Word Clouds

Data Science

A Layman’s View of an Agile Environment

Agile Software Development has gained traction in recent years, expanding its foundational values to many sectors outside of tech. For the uninitiated, the plethora of technical jargon can be very intimidating, and those seeking to enter a technical role need to at least have an understanding of an Agile environment. What is Agile? Purists will… Continue reading A Layman’s View of an Agile Environment

Data Science

Fraud Classification with AutoML

Introduction Data scientist follow a structure of obtaining data, cleaning it, and then feeding it through one of their many fancy models to determine which one has the best "predictive" capabilities. This insight is highly valued by many companies either as a means to have some foresight into future conditions or revise current systems to… Continue reading Fraud Classification with AutoML

Data Science

A Mathless Breakdown of Decisions Trees and the Gini Impurity Index

The decision tree algorithm is one of the first learned by most aspiring data scientists because while the underlying math may be tedious, the overall logic is pretty simple to understand, at least on a surface level. At its core, a decision tree is a classifier algorithm, which means it has to make a decision… Continue reading A Mathless Breakdown of Decisions Trees and the Gini Impurity Index

Data Science

Evaluating Hospital Effectiveness: The First of Many Failures

  It's fine to celebrate success, but it is more important to heed the lessons of failure. -Bill Gates A Preface: To be blunt, I have failed. More accurately, my models have failed (by ironically being not accurate, all pun intended). Despite weeks of work, I have failed to provide anything conclusive about the objective… Continue reading Evaluating Hospital Effectiveness: The First of Many Failures