Surprising Uses of Synthetic Random Data Sets
I have used synthetic data sets many times for simulation purposes, most recently in my articles Six degrees of Separations between any two Datasets and How to Lie wit...
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Surprising Uses of Synthetic Random Data Sets
I have used synthetic data sets many times for simulation purposes, most recently in my articles Six degrees of Separations between any two Datasets and How to Lie with p...
Want to be data-driven? Better start thinking about DataOps
Everyone’s talking data. Data is the key to unlocking insight, the secret sauce that will help you get predictive, the fuel for business intelligence. The transformativ...
Multilevel Modelling of U.S. Home Loan Data
The housing market has undergone quite a change in the past decade, with more stringent lending criteria for housing having been enforced. A key objective of financial in...
Exploratory Data Analysis with Python
In addition to being the sexiest job of the twenty-first century, Data Science is new electricity as quoted by Andrew Ng. A lot of professionals from various discipline...
Writing/Reading Large R dataframes/data.tables — Addendum.
After posting my most recent blog using census data to illustrate handling “large” dataframes in R exploiting fst and feather file formats, I realized I c...
10 Myths About Data Scientists
In the nascent field of Data Science, myths are abound. Here’s my top 10, scoured from the internet (where better than to find a myth or two?). Myth #1: It’s ...
DSC Webinar Series: Optimize the Data Supply Chain
Every organization is aiming to produce more comprehensive understanding of their customers, their business operations and their risks, through data. Most organizations a...
Taming 1.5 Billion Rows of "Big Apple” Data
Diving into the many underlying trends throughout the entire 1.5 Billion rows of NYC Taxi data with Pivot Billion The age of data has arrived. With it, more and more data...
One Shot Learning and Other Strategies for Reducing Training Data
Summary: Not enough labeled training data is a huge barrier to getting at the equally large benefits that could be had from deep learning applications. Here are five st...