Hello, I'm a computer science graduate with a passion for data science and artificial intelligence. With four years of experience as a full-stack web developer using Python Django and React, I've recently delved into the world of data science and machine learning. I'm fascinated by the power of extracting valuable insights from data, and I've been working with tools like Keras, RapidMiner and Python's scikit-learn to clean and analyze datasets. I look forward to leveraging these skills to create something amazing with AI in the future.
LinkedInWelcome to my ML skills showcase, where I dive into real-world data challenges and solutions. Explore the practical applications of my data science and machine learning skills through these engaging projects.
In this case study, the aim is to classify images from the Amazon Berkeley Objects (ABO) Dataset into product categories and subcategories. We encountered a complex dataset, but after implementing various solutions, satisfactory results were achieved.
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In this case study, I will employ a variety of machine learning techniques and algorithms to develop an optimal predictive model for chronic kidney disease based on historical data.
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A partir de Regresión Logística en Python, se busca predecir si un paciente que ya experimentó un ataque al corazón experimentará uno nuevo basándonos en aspectos de su vida y salud.
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Usando Python + scikit-learn y Rapidminer, analizo el uso de árboles de decisión para la clasificación de flores Iris, comparando los resultados en ambas plataformas y visualizando los árboles resultado.
BlogThis section presents initial investigations that can serve as a starting point for interesting case studies to explore further in the future.
In this case study, we investigate and analyze data on government purchases under the Open Contracting Data Standard (OCDS).
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