I have a close circle of clued-on/tech savvy friends whose views I take seriously. For the last few weeks, one of these friends has been… Read More »IOTA – The potential to drive Data Science for IoT
A fictitious retailer which I am calling Malwart sells automobiles and automotive parts. On this blog I will be focused on the sale of a… Read More »Character Analysis in Production and Sales
This article was written by Andy at Adventures in Deep Learning. Fully connected neural network example architecture In previous tutorials on deep learning, I have… Read More »Microsoft CNTK Tutorial: Build a Neural Network with Python
This article is written by Giuseppe Bonaccorso. One of the most interesting effects of PCA (Principal Component Analysis) is to decorrelate the input covariance matrix C,… Read More »PCA with Rubner-Tavan Networks
I originally wrote this article on LinkedIn. While there is a host of articles that focus on mechanics and methods in Data Science and Data… Read More »Attachment In The Digital Age.
Data mining is the process of looking at large banks of information to generate new information. Intuitively, you might think that data “mining” refers to… Read More »The 7 Most Important Data Mining Techniques
This post is dedicated to all the R Lovers…Flaunt your knowledge of R programming in your peer group with the following code. Wish Christmas with… Read More »Wish Christmas with R
For long, insurance firms have been relying on traditional virtual assistants. But with the advent of improved analytics, insurance technology startups (better known as Insurtech)are… Read More »Artificial Intelligence (AI) Disrupts the Traditional Insurance Industry
Market Mix Modeling (MMM) is a technique which helps in quantifying the impact of several marketing inputs on sales or Market Share. The purpose of… Read More »Market Mix Modeling (MMM)
This article was written by Jim Frost. The standard error of the regression (S) and R-squared are two key goodness-of-fit measures for regression analysis. While R-squared… Read More »Standard Error of the Regression vs. R-squared
