Acerca de este Curso
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Aprox. 12 horas para completar

Sugerido: 17 hours/week...

Inglés (English)

Subtítulos: Inglés (English)
User
Los estudiantes que toman este Course son
  • Data Scientists
  • Machine Learning Engineers
  • Chief Technology Officers (CTOs)
  • Data Engineers
  • Research Assistants
User
Los estudiantes que toman este Course son
  • Data Scientists
  • Machine Learning Engineers
  • Chief Technology Officers (CTOs)
  • Data Engineers
  • Research Assistants

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel avanzado

Aprox. 12 horas para completar

Sugerido: 17 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
4 horas para completar

Working with Sequences

14 videos (Total 41 minutos), 1 lectura, 4 cuestionarios
14 videos
Getting Started with Google Cloud Platform and Qwiklabs3m
Sequence data and models5m
From sequences to inputs2m
Modeling sequences with linear models2m
Lab intro: using linear models for sequences20s
Lab solution: using linear models for sequences7m
Modeling sequences with DNNs2m
Lab intro: using DNNs for sequences19s
Lab solution: using DNNs for sequences2m
Modeling sequences with CNNs3m
Lab intro: using CNNs for sequences19s
Lab solution: using CNNs for sequences3m
The variable-length problem4m
1 lectura
How to send course feedback10m
1 ejercicio de práctica
Working with Sequences
15 minutos para completar

Recurrent Neural Networks

4 videos (Total 15 minutos), 1 cuestionario
4 videos
How RNNs represent the past4m
The limits of what RNNs can represent5m
The vanishing gradient problem1m
1 ejercicio de práctica
Recurrent Neural Networks
4 horas para completar

Dealing with Longer Sequences

14 videos (Total 62 minutos), 4 cuestionarios
14 videos
LSTMs and GRUs6m
RNNs in TensorFlow2m
Lab Intro: Time series prediction: end-to-end (rnn)45s
Lab Solution: Time series prediction: end-to-end (rnn)10m
Deep RNNs1m
Lab Intro: Time series prediction: end-to-end (rnn2)26s
Lab Solution: Time series prediction: end-to-end (rnn2)6m
Improving our Loss Function2m
Demo: Time series prediction: end-to-end (rnnN)3m
Working with Real Data10m
Lab Intro: Time Series Prediction - Temperature from Weather Data1m
Lab Solution: Time Series Prediction - Temperature from Weather Data11m
Summary1m
1 ejercicio de práctica
Dealing with Longer Sequences
Semana
2
2 horas para completar

Text Classification

8 videos (Total 35 minutos), 2 cuestionarios
8 videos
Text Classification6m
Selecting a Model2m
Lab Intro: Text Classification47s
Lab Solution: Text Classification11m
Python vs Native TensorFlow4m
Demo: Text Classification with Native TensorFlow7m
Summary1m
1 ejercicio de práctica
Text Classification
1 hora para completar

Reusable Embeddings

6 videos (Total 28 minutos), 2 cuestionarios
6 videos
Modern methods of making word embeddings8m
Introducing TensorFlow Hub1m
Lab Intro: Evaluating a pre-trained embedding from TensorFlow Hub24s
Lab Solution: TensorFlow Hub9m
Using TensorFlow Hub within an estimator1m
1 ejercicio de práctica
Reusable Embeddings
3 horas para completar

Encoder-Decoder Models

10 videos (Total 84 minutos), 3 cuestionarios
10 videos
Attention Networks4m
Training Encoder-Decoder Models with TensorFlow6m
Introducing Tensor2Tensor11m
Lab Intro: Cloud poetry: Training custom text models on Cloud AI Platform1m
Lab Solution: Cloud poetry: Training custom text models on Cloud AI Platform25m
AutoML Translation4m
Dialogflow6m
Lab Intro: Introducing Dialogflow54s
Lab Solution: Dialogflow13m
1 ejercicio de práctica
Encoder-Decoder Models
14 minutos para completar

Summary

1 video (Total 4 minutos), 1 lectura
1 video
1 lectura
Additional Reading10m
4.5
26 revisionesChevron Right

50%

comenzó una nueva carrera después de completar estos cursos

67%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

Principales revisiones sobre Sequence Models for Time Series and Natural Language Processing

por PRAug 11th 2019

Great way to practically learn a lot of stuff. Sometimes, a lot of it starts to go over head. But, it is completely worth the learning curve! Definitely recommend it!

por JWNov 11th 2018

Excellent course for those who know RNN. Knowledge is refreshed and techniques are consolidated. More details about Google ecosystem is introduced.

Acerca de 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....

Acerca de Programa especializado Advanced Machine Learning with TensorFlow on Google Cloud Platform

This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems. Topics introduced in earlier courses are referenced in later courses, so it is recommended that you take the courses in exactly this order....
Advanced Machine Learning with TensorFlow on Google Cloud Platform

Preguntas Frecuentes

  • Sí, puedes acceder a una vista preliminar del primer video y ver el programa antes de inscribirte. Debes comprar el curso para acceder a contenido que no está incluido en la vista preliminar

  • Si decides inscribirte en el curso antes de la fecha de inicio de la sesión, tendrás acceso a todos los videos y las lecturas de la lección para el curso. Podrás enviar tareas en cuanto comience la sesión.

  • Una vez que te inscribes y comienza la sesión, tendrás acceso a todos los videos y otros recursos, incluidos artículos de lectura y el foro de debate del curso. Podrás ver y enviar tareas de práctica y completar tareas con calificación obligatorias para obtener un título y un Certificado de curso

  • Si completas el curso de manera correcta, tu Certificado de curso electrónico se agregará a la página Logros. Desde allí, puedes imprimir tu Certificado de curso o agregarlo a tu perfil de LinkedIn

  • Este curso es uno de los pocos que se ofrecen en Coursera que está actualmente disponible solo para estudiantes que pagaron o que recibieron ayuda económica, si está disponible.

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