Google Cloud
Art and Science of Machine Learning en EspaƱol
Google Cloud

Art and Science of Machine Learning en EspaƱol

3,285 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.7

(51 reviews)

Intermediate level
Some related experience required
19 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.7

(51 reviews)

Intermediate level
Some related experience required
19 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Generalizar un modelo de AA usando tĆ©cnicas de regularización

  • Ajustar el tamaƱo del lote y la tasa de aprendizaje para mejorar el rendimiento del modelo

  • Optimizar el modelo

  • Aplicar los conceptos en el código de TensorFlow

Details to know

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Assessments

7 assignments

Taught in Spanish

Build your subject-matter expertise

This course is part of the Machine Learning with TensorFlow on Google Cloud en EspaƱol Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 7 modules in this course

Le damos la bienvenida a The Art and Science of Machine Learning. En este curso, se abordan las habilidades bÔsicas de intuición, buen criterio y experimentación del AA necesarias para ajustar mejor y optimizar modelos de AA a fin de lograr el mejor rendimiento. AprenderÔ a generalizar su modelo usando técnicas de regularización y descubrirÔ los efectos de los hiperparÔmetros, como el tamaño del lote y la tasa de aprendizaje, en el rendimiento del modelo. Analizaremos algunos de los algoritmos de optimización de los modelos mÔs comunes y le mostraremos cómo especificar un método de optimización en su código de TensorFlow.

What's included

1 video

En este módulo, aprenderÔ a ajustar el tamaño del lote y la tasa de aprendizaje para mejorar el rendimiento del modelo, optimizar su modelo y aplicar los conceptos en el código de TensorFlow.

What's included

8 videos2 readings1 assignment1 app item

En este módulo, aprenderÔ a diferenciar entre parÔmetros e hiperparÔmetros. Luego, veremos el enfoque tradicional de búsqueda por cuadrícula y aprenderemos a ir mÔs allÔ mediante algoritmos mÔs inteligentes. Por último, verÔ cómo Cloud ML Engine facilita la automatización del ajuste de hiperparÔmetros.

What's included

5 videos1 reading1 assignment2 app items

En este módulo, comenzaremos a presentar la ciencia junto con el arte del aprendizaje automÔtico. Primero, hablaremos sobre cómo realizar una regularización para lograr dispersión y, de este modo, conseguir modelos mÔs simples y concisos. Luego, abordaremos la regresión logística y aprenderemos a determinar el rendimiento.

What's included

5 videos2 readings2 assignments

En este módulo, profundizaremos en la ciencia, específicamente en las redes neuronales.

What's included

7 videos1 reading2 assignments2 app items

En este módulo, aprenderÔ a usar incorporaciones para administrar los datos dispersos, a fin de que los modelos de aprendizaje automÔtico que usan ese tipo de datos consuman menos memoria y se entrenen mÔs rÔpido. Las incorporaciones también son una forma de reducir la dimensionalidad. Esto hace que los modelos sean mÔs simples y generalizables.

What's included

8 videos1 reading1 assignment1 app item

Resumen de los puntos clave de aprendizaje del curso.

What's included

1 video3 readings

Instructor

Instructor ratings
4.5 (16 ratings)
Google Cloud Training
Google Cloud
1,795 Courses3,296,994 learners

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Google Cloud

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4.7

51 reviews

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