This rubric covers the use of statistical tools working on large datasets to create models and derive inferences, as well as coverage of the field in its entirety. This differs from machine learning primarily in that the latter focuses on functional gradient analysis or neural networks (kernels) to derive models.
With more than 40.000 searches happening in Google per second, Google Trends is a powerful tool that allows us to visualize searching behavior and uncover… Read More »Step by Step Guide to Build a Google Trends Scraper Using PyTrends
When you build a business with a vision to build the best product, it becomes immensely difficult to follow through without knowing how it’s performing… Read More »5 Reasons To Use Power BI For Business Analytics
This article is part of a series about fun problems, offered with solutions. The previous one can be found here. This new problem falls in… Read More »Fun Mathematical Problem in Stochastic Geometry: Random Triangles
I am not a medical doctor, only a doctor in statistical science. Yet much of the political crisis has its origin rooted in data and… Read More »Covid: Predictions for the Next Ten Years
A hundred years of modeling didn’t help forecast the extent of the current pandemic. Hundreds of thousands of deaths could have been prevented with better… Read More »The Future of Pandemic Modeling
Summary Clustering analysis is another standard method available with SAP BW Data Mining. The clustering models based on this method may apply various combinations of… Read More »SAP BW Data Mining Analytics: Clustering Reporting (Part 4, final)
Background Every industry will be affected by algorithms and algorithmic bias. But we could rethink this as Do algorithms introduce bias or do they… Read More »Do algorithms introduce bias or do they promote transparency?
This article has been excerpted from my book, Models and Algorithms for Unlabelled Data. Next time you visit a nearby grocery store, look around inside… Read More »Equivalence class clustering and bottom-up lattice traversal (ECLAT)
What is Sentiment Analysis? Sentiment analysis can be defined as analyzing the positive or negative sentiment of the customer in text. The contextual analysis of… Read More »Applications of Sentiment Analysis
Picture Courtesy: Freepik The article explains the algorithm behind the recently introduced Python package named PyHard, based on the concept of Instance Space Analysis. It… Read More »PyHard – A tool to assess dataset quality and identify hard-to-classify instances in general
