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.

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Advanced Statistical Modeling for Predictive Analytics in International Construction: A Practical Guide

Introduction: Predictive Analytics in International Construction In the high-stakes world of international construction, where projects often span continents and budgets, the ability to predict outcomes accurately is paramount. Cost overruns, schedule delays, and unforeseen risks can cripple even the most meticulously planned ventures. Advanced statistical modeling offers a powerful toolkit to mitigate these challenges, transforming
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Bayesian Inference for A/B Testing: A Practical Guide with Python Examples

Introduction: Beyond Frequentist A/B Testing with Bayesian Inference In the ever-evolving landscape of data-driven decision-making, A/B testing stands as a cornerstone for optimizing user experiences and business outcomes. Traditional frequentist approaches have long dominated this domain, but a powerful alternative is gaining traction: Bayesian inference. This article provides a comprehensive guide to Bayesian A/B testing,
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Advanced Statistical Inference Technologies: Unlocking Insights in the Data Age

The Dawn of Advanced Statistical Inference In an era defined by a deluge of data, the ability to extract meaningful insights from complex datasets has become not just advantageous, but absolutely paramount. Advanced statistical inference technologies stand at the forefront of this endeavor, offering sophisticated tools to model uncertainty, estimate parameters, and make predictions with
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