Overview and simple trial of Convolutional Neural Network with MXnet
Actually I’ve known about MXnet for weeks as one of the most popular library / packages in Kaggler, but just recently I heard bug fix has been almost done and some ...
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Ten Signs of Data Science Maturity – Free eBook
Kirk Borne and I recently published “Ten Signs of Data Science Maturity” free O’Reilly ebook (http://www.oreilly.com/data/free/ten-signs-of-data-science...
Variance, Clustering, and Density Estimation Revisited
Introduction We propose here a simple, robust and scalable technique to perform supervised clustering on numerical data. It can also be used for density estimation, and e...
Citizen Data Scientist – Care, Feeding, and Control
Summary: Management values the self-starting, data-driven, curious, and urgent characteristics that define the Citizen Data Scientist. But the path to encouraging the...
Regression, Logistic Regression and Maximum Entropy
One of the most important tasks in Machine Learning are the Classification tasks (a.k.a. supervised machine learning). Classification is used to make an accurate predicti...
Don't Buy Machine Learning
Author: Marcos Sponton A few comments for those who are about to invest on Machine Learning intensive project During a conversation I had with Peter Norvig, we discussed ...
How to forecast using Regression Analysis in R
Regression is the first technique you’ll learn in most analytics books. It is a very useful and simple form of supervised learning used to predict a quantitative respon...
The Curse of #DataViz
With the wide array of amazing data visualization tools out there – SAP Lumira, Qlik, Domo, Tableau – you would think that the world has moved towards a graph...
Bridging the Gap Between Data Science and DevOps
What’s the real value of data science? Hailed as the sexiest job of the 21st century just a few years ago, there are rumors that it’s not quite proving its worth. Gia...
15 Most Controversial Data Science Articles
These articles were controversial in the sense that they highlighted the differences between data science and other disciplines, at a time when many believed that data sc...