Informações sobre o curso
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100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível intermediário

Nível intermediário

Horas para completar

Aprox. 5 horas para completar

Sugerido: 2 semanas de estudio, de 5 a 7 horas por semana...
Idiomas disponíveis

Espanhol

Legendas: Espanhol, Francês, Portuguese (Brazilian), Alemão, Japonês...
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível intermediário

Nível intermediário

Horas para completar

Aprox. 5 horas para completar

Sugerido: 2 semanas de estudio, de 5 a 7 horas por semana...
Idiomas disponíveis

Espanhol

Legendas: Espanhol, Francês, Portuguese (Brazilian), Alemão, Japonês...

Programa - O que você aprenderá com este curso

Semana
1
Horas para completar
1 minutos para concluir

Introducción

¿Desea saber cómo mejorar la precisión de sus modelos de AA? ¿Cuál es la forma de saber qué columnas de datos se prestan para las funciones más útiles? Bienvenido a Feature Engineering, el curso en el que hablaremos de cómo reconocer buenas funciones, y cómo puede preprocesarlas y transformarlas para usarlas de forma óptima en sus modelos....
Reading
1 vídeos (Total de 1 min)
Horas para completar
2 horas para concluir

Conversión de datos sin procesar en funciones

La ingeniería de funciones es a menudo la etapa más larga y más difícil en el desarrollo de un proyecto de AA. En el proceso de ingeniería de funciones, comienza con los datos sin procesar y usa su propio conocimiento del dominio para crear funciones que hagan funcionar sus algoritmos de aprendizaje automático. En este módulo, exploraremos qué hace que una función sea buena y cómo representarla en su modelo de AA....
Reading
14 vídeos (Total de 52 min), 3 testes
Video14 videos
Funciones buenas y malas2min
Cuestionario: Las funciones se relacionan con el objetivo3min
Funciones conocidas en el momento de la predicción3min
Cuestionario: Las funciones que se pueden conocer en el momento de la predicción4min
Las funciones deben ser numéricasmin
Cuestionario: Las funciones deben ser numéricas5min
Las funciones deben tener suficientes ejemplos1min
Cuestionario: Las funciones deben tener suficientes ejemplos (primera parte)2min
Cuestionario: Las funciones deben tener suficientes ejemplos (segunda parte)2min
El aporte de las estadísticas manualesmin
Representación de funciones8min
AA y estadísticas3min
Solución del lab: Mejore la exactitud del modelo con funciones nuevas12min
Quiz2 exercícios práticos
Conversión de datos sin procesar en funciones6min
Representación de las funciones6min
Horas para completar
4 horas para concluir

Preprocesamiento y creación de funciones

En esta sección del módulo, se tratarán el preprocesamiento y la creación de funciones, que son técnicas de procesamiento de datos que pueden ayudarlo a preparar un conjunto de funciones para un sistema de aprendizaje automático. ...
Reading
10 vídeos (Total de 52 min), 6 testes
Video10 videos
Beam y Dataflow9min
Introducción al lab: Canalización simple de Dataflowmin
Solución del lab: Canalización simple de Dataflow6min
Canalizaciones de datos que se escalan5min
Introducción al lab: MapReduce en Dataflowmin
Solución del lab: MapReduce en Dataflow3min
Procesamiento previo con Cloud Dataprep6min
Introducción al lab: Procesamiento de atributos con ventanas de tiempo en Cloud Dataprep10min
Solución del lab: Procesamiento de atributos con ventanas de tiempo en Cloud Dataprepmin
Quiz3 exercícios práticos
Preprocesamiento y creación de funciones14min
Apache Beam y Cloud Dataflow14min
Preprocesamiento con Cloud Dataprep4min
Horas para completar
3 horas para concluir

Combinaciones de funciones

En el aprendizaje automático tradicional, las combinaciones de funciones no juegan un papel muy importante, pero con los métodos actuales de AA, estas combinaciones son una herramienta muy valiosa. En este módulo, aprenderá a reconocer los tipos de problemas en los que las combinaciones de funciones representan una excelente manera de ayudar al aprendizaje automático....
Reading
18 vídeos (Total de 90 min), 2 testes
Video18 videos
¿Qué es una combinación de atributos?5min
Discretización1min
Memorización y generalización4min
Colores de taxi4min
Introducción al lab: Combinaciones de atributos para crear un buen clasificadormin
Solución del lab: Combinaciones de atributos para crear un buen clasificador6min
Dispersión y cuestionario5min
Introducción al lab: Algo bueno en excesomin
Solución del lab: Algo bueno en exceso7min
Implementación de combinaciones de atributos5min
Incorporación de combinaciones de atributos9min
Dónde se puede realizar la ingeniería de funciones6min
Creación de atributos en TensorFlow2min
Creación de atributos en DataFlow2min
Introducción al lab Mejore los modelos de AA con la ingeniería de funcionesmin
Solución del lab (primera parte): Informe de equidad del AA3min
Solución del lab (segunda parte): Mejore los modelos de AA con la ingeniería de funciones20min
Quiz1 exercícios práticos
Combinaciones de funciones8min
Horas para completar
2 horas para concluir

TF Transform

TensorFlow Transform (tf.Transform) es una biblioteca para preprocesar datos con TensorFlow. Es útil para el preprocesamiento que requiere un pasaje completo de los datos, como la normalización de un valor de entrada según la media y la desviación estándar, la conversión a entero de un vocabulario mediante un examen de todos los ejemplos de entradas para los valores, la organización en depósitos de las entradas según la distribución de datos observada. En este módulo, exploraremos los casos prácticos para tf.Transform....
Reading
7 vídeos (Total de 42 min), 2 testes
Video7 videos
TensorFlow Transform8min
Fase de análisis3min
Fase de transformación4min
Asistencia para entrega3min
Introducción al lab Exploración de tf.transform1min
Solución del lab Exploración de tf.transform19min
Quiz1 exercícios práticos
tf.transform6min
Horas para completar
3 minutos para concluir

Resumen

Aquí resumimos los puntos más importantes aprendidos en cada módulo sobre la ingeniería de funciones: Cómo seleccionar buenas funciones, cómo preprocesar a gran escala, cómo usar combinaciones de funciones y cómo practicar con TensorFlow....
Reading
1 vídeos (Total de 3 min)
Video1 videos

Sobre Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

Sobre o Programa de cursos integrados Machine Learning with TensorFlow on Google Cloud Platform en Español

>>>Si se inscribe en esta especialización acepta las Condiciones del Servicio de Qwiklabs, que se establecen en las Preguntas Frecuentes. Puede consultarlas en https://qwiklabs.com/terms_of_service.<<< ***Google Cloud y Kaggle desean invitarlo a participar en nuestra competencia amistosa de predicción de tarifas de taxis de Nueva York, que se está realizando en este momento. Para obtener más información, visite: https://www.kaggle.com/c/new-york-city-taxi-fare-prediction.*** ¿Qué es el aprendizaje automático? ¿Qué tipos de problemas puede solucionar? ¿Cuáles son las cinco fases para convertir un posible caso práctico en un recurso que pueda aprovechar la tecnología de aprendizaje automático? ¿Por qué es importante no saltarse fases? ¿Por qué las redes neuronales son tan populares? ¿Cómo podría plantear un problema de aprendizaje supervisado y encontrar una buena solución generalizable mediante un descenso de gradientes y una forma meditada de crear conjuntos de datos? Aprenda a escribir modelos de aprendizaje automático distribuido que escalen en Tensorflow, que escalen de forma horizontal en el entrenamiento de esos modelos y que brinden predicciones de alto rendimiento. Convierta los datos sin procesar en funciones de una forma que permita al AA aprender características importantes de los datos y aportar una percepción humana para abordar los problemas. Por último, aprenda a incorporar la combinación adecuada de parámetros que desarrolle modelos generalizados y exactos, y conozca la teoría para solucionar determinados tipos de problemas de AA. Experimentará con el AA de extremo a extremo, a partir de la construcción de una estrategia centrada en el AA y el avance hacia el entrenamiento, optimización y producción de modelos con labs prácticos mediante Google Cloud Platform....
Machine Learning with TensorFlow on Google Cloud Platform en Español

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