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Objetivos

01

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

02

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

03
04

Perfil de Estudiante

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Temario

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

Evaluación y proyectos

SUSCRÍBETE AL CURSO

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Bourbaki Finanzas

Fundamentos de Machine Learning

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Estudiar los fundamentos matemáticos y estadísticos que permitan comprender los detalles y las sutilezas de algunos modelos comúnmente utilizados en Machine Learning.

Familiarizar al estudiante con el análisis formal de las aplicaciones de Machine Learning a problemas concretos, de tal modo que al final del curso sea capaz de identificar las características que determinan un modelo exitoso.

Desarrollar en el alumno una sólida intuición y robusta formación técnica que le permita acercarse con confianza a la literatura sobre Machine Learning.

Temario

  • Perceptrón para la clasificación (primera red neuronal)
  • Espacios euclidianos y producto punto
  • Separación lineal
  • El algoritmo del Perceptrón
  • Caso no-separable linealmente y expresividad de las redes neuronales
  • Regularización el concepto de margen
  • Regresión lineal para forecasting (caso inyectivo)
  • Espacios de probabilidad y variables aleatorias
  • Independencia estadística
  • Distribuciones Gaussianas y de Laplace
  • Método del gradiente y optimización
  • Teorema de Bayes e interpretación bayesiana de la regresión
  • Ridge y Lasso
  • Árboles de decisión (bases de datos relacionales)
  • Interpretación geométrica y definición formal
  • El concepto de entropía
  • Algoritmos de entrenamiento
  • Random Forests
  • Regresiones logísticas (procesamiento del lenguaje)
  • El modelo logístico
  • Algoritmos de entrenamiento
  • Tests estadísticos
  • Regularización
  • Fundamentos de Machine Learning
  • Redes convolucionales (procesamiento de imágenes)
  • El concepto de tensor
  • Ideas detrás de la convolución
  • Algunas arquitecturas para el procesamiento de imágenes
  • Back-propagation


Profesores del curso

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