50 IoT (Internet of Things) Predictions for 2016
IoT and data science are intertwined, as sensor data from wearables, transportation or healthcare systems, manufacturing and engineering, needs to be collected, refined, ...
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How to Plan Your Next BI Project
A Three Step Guide for BI Professionals Launching a new business intelligence initiative or project can be tricky: while we’re staunch believers in agile BI and quick w...
Designing better algorithms: 5 case studies
In this article, using a few examples and solutions, I show that the “best” algorithm is many times not what data scientists or management think it is. As a r...
Big data: Millennials on Social Media – digging a little deeper
Guest blog post byRick Riddle It can be tempting to lump all the people who’ve spent more of their life with social media as one large group with largely the same inter...
Fast Forward transformation with SPARK
Fast forward transformation process in data science with Apache Spark Data Curation : Curation is a critical process in data science that helps to prepare data for featur...
Price Optimisation Using Decision Tree (Regression Tree) – Machine Learning
INTRODUCTION TO THE RESEARCH QUESTION The research was conducted to find out what price maximises profit without sacrificing the high demand for the product due to the ...
11 Great Hadoop, Spark and Map-Reduce Articles
This reference is a part of a new series of DSC articles, offering selected tutorials, references/resources, and interesting articles on subjects such as deep learning, m...
The Case for a New “Final Frontier” in Data Analytics
This article has been contributed by Alain Louchez (Georgia Tech Research Institute) The Internet of Things already integrates a new phase beyond prescriptive analytics....
Comparison Between Global Vs Local Normalization of Tweets, and Various Distances
In the previous example we used clustering to see if an apparent pattern exists within Brexit tweets. We found out that we have three distinct patterns, the leave, the...
Machine Learning vs. Traditional Statistics: Different philosophies, Different Approaches
“Machine Learning (ML)” and “Traditional Statistics(TS)” have different philosophies in their approaches. With “Data Science” in the f...