Data Science and Databases

Listening is everything—especially when it comes to effective marketing and product design. Gain key market insights from social media data using sentiment analysis and topic modeling in Python.

Explore Twitter data clusters to discover keywords that dominate identified groups. Focusing on a politically slanted data set provides an easy target for analysis.

Improving supply chains is a top priority worldwide. Discover how mathematical optimization and Python coding can help keep a complex supply chain competitive.

Clustering in machine learning has a variety of applications, but how do you know which algorithm is best suited to your data? Here's how to amplify your data insights with comparison metrics, including the F-measure.

Python and R empower data scientists to solve problems using elegant syntactic sugar, simplifying coding and solution exploration. Each language brings its unique capabilities and approach to bear.

Microsoft's Power BI is one of the most popular software solutions used to perform social network analysis. Here's how to create custom Power BI visuals in R for compelling and flexible results.

Understanding total spend is a common challenge for cloud users, especially on projects with complex pricing models. This article explores the top AWS cost optimizations that will help you scale your platform effectively.

Centrality and text analysis allow users to get more out of their social network data. Here’s how you can leverage them using R and Gephi.