Taylor Scott Amarel

Experienced developer and technologist with over a decade of expertise in diverse technical roles. Skilled in data engineering, analytics, automation, data integration, and machine learning to drive innovative solutions.

Categories

Mastering Bayesian Inference: A Practical Guide for Data Scientists

Unlocking the Power of Bayesian Inference: A Data Scientist’s Guide In the ever-evolving landscape of data science, practitioners are constantly seeking robust and flexible statistical methods to extract meaningful insights from complex datasets. Bayesian inference offers a powerful alternative to traditional frequentist approaches, providing a framework for incorporating prior knowledge, quantifying uncertainty, and making probabilistic

A Comprehensive Guide to Bayesian Inference for A/B Testing: Improve Decision-Making with Statistical Rigor

The Bayesian Revolution in A/B Testing: A New Era for Events and Entertainment In the high-stakes world of events and entertainment, where split-second decisions can make or break a campaign, traditional A/B testing methodologies are often found wanting. The frequentist approach, with its reliance on p-values and fixed sample sizes, struggles to provide the nuanced,