This one’s for the Oddballs
Introduction A very interesting paper was brought to my attention which proposes an adjustment to the traditional Stochastic Gradient Descent approach called Oddball Stochastic Gradient…
The Likelihood Function
Introductory Concepts In the field of statistics, researchers are interested in making inferences from data. The data is collected from a population; the data drawn…
Definitely Interesting Matrices
This is a post I've been wanting to write for a while - Quadratic forms and Definite matrices are everywhere in linear algebra and they…
Batch Updating with Plumber and Google Scheduler
Recently, I’ve had a chance to play with R’s plumber library and used it to run scripts on a schedule. This post will show how…
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Why You’re Not as Data-Driven as You Think You Are
How many times have you heard someone say they are data-driven or data centric or that “data is the heart of everything they do”? I’ve…
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Shortest Paths: Dijkstra’s Algorithm
Introduction I have a startling admission to make. When I was a student, I scoffed at Dijkstra's algorithm - I had paid it no mind…
Word2vec vs Fasttext – A First Look
Introduction Recently, I've had a chance to play with word embedding models. Word embedding models involve taking a text corpus and generating vector representations for…
Being a Data Scientist at a Start-Up
Although data science as a job function is relatively new compared to roles like software engineer or database administrator, in the age of “Big Data”,…
ML Classifier Evaluation – A First Look
Once you’ve built a machine learning classifier, the next step is to validate it and see how well it fits the data. This short post…
Naive and Proud: Introducing the Naive Bayes Algorithm
The Naive Bayes Algorithm is a simple and elegant approach for tackling supervised learning problems in Machine Learning. This post will be a brief introduction…
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