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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Quantization at the Edge: A Step-by-Step Guide to Optimizing Neural Networks for Real-World Deployment

The Edge AI Revolution Demands Smarter, Leaner Models As artificial intelligence migrates from cloud data centers to smartphones, wearables, and industrial sensors, the demand for efficient neural networks has never been greater. Edge devices face stringent constraints in memory, power, and compute, making model quantization a critical enabler of real-world AI. From fraud detection in

Revolutionizing Audio Clarity: A Step-by-Step Guide to Neural Network-Powered Super-Resolution

The Rise of Audio Super-Resolution: A New Frontier in Sound Quality The rise of audio super-resolution, powered by cutting-edge neural network technology, represents a transformative breakthrough in the pursuit of crystal-clear sound quality. As audio plays an increasingly central role in communication, entertainment, and content creation across various industries, the demand for enhanced audio experiences