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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Pruning vs. Quantization: A Deep Dive into Model Compression for Edge Deployment

AI at the Edge: Squeezing Intelligence into Small Spaces The relentless pursuit of artificial intelligence at the edge – from smart cameras analyzing traffic patterns to wearable devices monitoring vital signs – demands smaller, faster, and more energy-efficient machine learning models. Deploying complex neural networks on resource-constrained devices like Raspberry Pis and NVIDIA Jetson boards
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MLOps for OFW Families: Streamlining Data Science to Bridge the Distance

Bridging the Distance: MLOps for the Modern OFW Family For Overseas Filipino Worker (OFW) parents, the geographical distance separating them from loved ones presents profound challenges that extend beyond mere financial considerations. While remittances are crucial, nurturing and maintaining robust family bonds from afar demands innovative solutions. In the 2020s, Machine Learning Operations (MLOps) emerges
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Implementing Advanced Predictive Modeling with Python: A Practical Guide for Time Series Forecasting

Introduction: The Power of Time Series Forecasting In today’s data-driven world, the ability to predict future trends based on historical data is invaluable. Time series forecasting, a specialized branch of predictive modeling, focuses on analyzing data points collected over time to identify patterns and make informed predictions. From anticipating sales fluctuations to forecasting stock prices,
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Prophet vs. Greykite vs. NeuralProphet: A Comparative Guide to Time Series Forecasting

Forecasting the Future: A Deep Dive into Prophet, Greykite, and NeuralProphet The ability to accurately predict future trends based on historical data has become increasingly crucial across various sectors, from finance and retail to meteorology and resource management. Time series forecasting, a statistical technique used to predict future values based on past observations, has seen
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Selecting the Right Cross-Validation Technique and Model Performance Metrics for Regression Tasks

Introduction: The Importance of Rigorous Regression Model Evaluation In the rapidly evolving landscape of data science, building accurate and reliable regression models is paramount. However, simply training a model on a dataset isn’t enough. We need robust methods to assess its performance and ensure it generalizes well to unseen data. This is where cross-validation and
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Python Web Scraping for E-commerce Product Data: A Practical Tutorial

Introduction: Mining E-commerce Gold with Python Web Scraping In the rapidly evolving landscape of e-commerce, data is the new gold. The ability to extract, analyze, and leverage product data from online platforms provides a significant competitive advantage. Python, with its rich ecosystem of libraries, has emerged as the go-to language for web scraping. This comprehensive
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Building Scalable Data Pipelines for Machine Learning: A Practical Guide

Introduction: The Backbone of Scalable Machine Learning In the 2020s, machine learning (ML) has moved beyond experimentation and into production. But deploying ML models at scale presents a significant challenge: building robust and scalable data pipelines. These pipelines are the backbone of any successful ML application, responsible for ingesting, transforming, storing, and delivering data to
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Comprehensive Comparison: Python SDK Integration for Vertex AI, SageMaker, and Azure ML – A Developer’s Guide

Introduction: Navigating the Cloud ML Landscape with Python SDKs The democratization of machine learning has led to an explosion of cloud-based platforms offering comprehensive suites of tools and services. Among the leaders are Google’s Vertex AI, Amazon’s SageMaker, and Microsoft’s Azure Machine Learning. These platforms provide managed environments for the entire machine learning lifecycle, from
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Mastering Image Classification: A Comprehensive Guide to CNNs with TensorFlow 2.x

Unlocking Image Classification with TensorFlow: A Comprehensive Guide In an era where visual data reigns supreme, the ability to accurately and efficiently classify images has become paramount. From self-driving cars interpreting road signs, a critical application of Convolutional Neural Networks (CNNs) for autonomous navigation, to medical professionals diagnosing diseases from X-rays with enhanced Image Recognition
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Practical Time Series Data Manipulation and Visualization with Python: A Step-by-Step Tutorial

Introduction: Unlocking Insights from Time Series Data with Python Time series data is everywhere, silently narrating the stories of our world, from the minute-by-minute fluctuations of stock prices and the cyclical dance of weather patterns to the ebb and flow of website traffic and the critical rhythms of patient vital signs monitored in hospitals and
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