Breaking the Tyranny of Chalk Brackets in March Madness
March Madness is all about bold picks—except the safest way to win is playing it safe. Is that fair game or missing the point? Let’s break it down.
Business Insights Meet Analytics Skills in Anomaly Detection
Most analytics applications are built for regular data and normal processes—handling about 99% of use cases. But at business scale, the remaining 1% of irregular or anomalous cases can translate to millions or billions of data elements—each potentially connected to other data sets. This mixing of regular and irregular data can be a serious problem for machine learning or AI models that only expect to process typical data. But an opportunity hides here as well.
Likely Voters Models: The Key to Accurate Electoral Analysis
This article explores the most commonly used likely voter models, detailing how they identify people most likely to participate in an election. It examines methodologies such as self-reported voting intentions, past voting behavior, and demographic indicators.
Balancing AI Power with Human Insight: A Humorous Dive into Text Analytics
Extracting Knowledge and Making Decisions with Data Science
A Data Science Approach to Tallying Teslas on the Road
Curbing Fraud by Leveraging Analytics
How Often Does the Best Team Win the Title?
Machine Learning Engineers & Operations: Where DevOps Meet Data Science
How Good Am I at Ping Pong?
Credit Scoring in the Cryptocurrency Ecosystem
Get with the Times
Applying Computer Vision to Geospatial Analytics
Introduction to Domain Adversarial Neural Networks
Liftoff: The Basics of Predictive Model Deployment
Cross the Finish Line with Keras Sequential (Neural Network) Modeling
Efron, Simon, and the Bootstrap
Gambler’s Fallacy
Model Validation and Reproducibility of Results
Measuring Invisible Treatment Effects with Uplift Analysis: A Get-Out-The-Vote Example