Guest blog post by Gaurav Agrawal, COO at Soothsayer Analytics. In today’s world of big data and the internet of things, it is common for a business… Read More »Spectral Clustering – How Math is Redefining Decision Making
Is there a single “best” way to visualize data in a particular scenario and for a particular audience, or are there multiple “good enough” ways?… Read More »To Optimize or to Satisfice When Visualizing Data?
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… Read More »Overview and simple trial of Convolutional Neural Network with MXnet
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-maturity…). The ebook identifies the successful characteristics to help build… Read More »Ten Signs of Data Science Maturity – Free eBook
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,… Read More »Variance, Clustering, and Density Estimation Revisited
Summary: Management values the self-starting, data-driven, curious, and urgent characteristics that define the Citizen Data Scientist. But the path to encouraging these individuals also requires… Read More »Citizen Data Scientist – Care, Feeding, and Control
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 prediction… Read More »Regression, Logistic Regression and Maximum Entropy
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… Read More »How to forecast using Regression Analysis in R