In a previous post, I have provided a discussion of model stacking, a popular approach in data science competitions for boosting predictive performance. Since then, the ...
Note: This is a long post, but I kept it as a single post to maintain continuity of the thought flow In this longish post, I have tried to explain Deep Learning starting ...
Demystifying the Term Actionable Insights in Analytics Prashanth H Southekal and Matthew Joyce These days, the term Actionable Insights has become one of the most commo...
Summary: Despite hundreds of projects and thousands of data scientists devoted to bringing AI/ML to healthcare, adoption remains low and slow. A good portion of this ...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, ...
Introduction The boundaries of the enterprise are becoming diffused. You have data on the network, on the endpoint, and on the cloud. Enabling visibility into your data f...
Data Scientist is regarded as the sexiest job of the 21st century. It is a high paying lucrative jobs which comes with a lot of responsibility and commitment. Any profes...
This article was written by Laura Ellis. One of the reasons why I love R is that I feel like I’m constantly finding out about cool new packages through an ever-growi...
This article was written by Natalie Wolchover. Even as machines known as “deep neural networks” have learned to converse, drive cars, beat video games and Go cha...
Yep. And it’s a big one. There is a general consensus that when we talk about open data we are referring to any piece of data or content that is free to access, use, r...