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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Month: April 2025

Fine-Tuning Whisper: A Comprehensive Guide to Multilingual Speech Recognition

Introduction: Unleashing Whisper’s Multilingual Potential In an increasingly interconnected world, the ability to accurately transcribe speech across multiple languages is paramount. Open AI’s Whisper, a transformer-based automatic speech recognition (ASR) system, has emerged as a powerful tool in this domain. While Whisper exhibits impressive zero-shot performance across a wide range of languages, fine-tuning can significantly
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Comprehensive Comparison: Feast vs. Tecton vs. Hopsworks for Cloud-Based Feature Stores (2024)

The Feature Store Frontier: Feast, Tecton, and Hopsworks in 2024 The race to operationalize machine learning models has led to the rise of feature stores – centralized repositories for managing and serving features to models in both training and production environments. As machine learning matures, the ability to consistently and reliably generate and serve features
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Arming Against AI Sabotage: A Deep Dive into Adversarial Machine Learning Libraries

The Silent Threat: Adversarial Attacks on Machine Learning In the high-stakes arena of artificial intelligence, where algorithms increasingly govern critical decisions, a subtle but profound threat looms: adversarial attacks. These are carefully crafted inputs designed to fool machine learning models, causing them to misclassify data with potentially devastating consequences. Imagine a self-driving car misinterpreting a
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Canary Deployments for Machine Learning: A Comprehensive Guide

Introduction: The Canary in the Machine Learning Coal Mine In the ever-evolving landscape of machine learning, deploying models to production is a critical step. However, simply pushing a new model live can be fraught with risks. A sudden drop in performance, unexpected biases, or infrastructure bottlenecks can all lead to significant disruptions. Enter canary deployments,
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NCF vs. MF: A Deep Dive into Recommendation Algorithms

Introduction: The Rise of Personalized Recommendations In the realm of personalized experiences, recommendation systems have become indispensable. From suggesting the next binge-worthy series on streaming platforms to curating product recommendations on e-commerce sites, these systems shape our digital interactions. Two prominent techniques that have powered recommendation engines over the past decade (2010-2019) are Matrix Factorization
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