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Redes Neuronales Básicas aplicadas a Ciencia de Datos
Sobre el curso
Curso corto para asimilar los principios fundamentales de las Redes Neuronales aplicadas a la Ciencia de Datos, impulsando tu capacidad de construir modelos predictivos. En este taller intensivo, explorarás las diferencias entre redes unicapa y multicapa, implementarás modelos básicos utilizando librerías esenciales como Numpy y PyTorch, y lograrás entrenar y evaluar su rendimiento. Es la vía directa para transformar conceptos teóricos en soluciones prácticas de Machine Learning.
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Redes Neuronales Básicas aplicadas a Ciencia de Datos
Valentina Martinez
01 de junio, 2026
Explora el learning path completo
Aprenderás a construir modelos predictivos dominando los fundamentos de las Redes Neuronales y Machine Learning. Implementarás modelos unicapa y multicapa utilizando librerías esenciales como Numpy y PyTorch, y mejorarás el rendimiento del modelo a través de la optimización de arquitectura. Conecta los principios teóricos con la implementación práctica para llevar tu capacidad analítica y tu carrera en Ciencia de Datos al siguiente nivel.
1/
6
Fundamentos esenciales de redes neuronales
2/
6
Redes Unicapa y Multicapa: Implementación con Numpy
3/
6
Dominando PyTorch: Tensores, Autograd y Modelos
4/
6
Entrenamiento Efectivo y Evaluación de Modelos
5/
6
Optimización de Arquitectura y Activaciones en Redes Neuronales
6/
6
Evaluación Integral de Redes Neuronales
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33.161 14.705 32.322 15.102 Z" fill="rgb(162, 153, 138)" height="29.052077929999996px" id="Fg0VyQnrb" transform="translate(1.5 7.5)" width="111.9950317428963px"/></svg>)
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