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#### 100% online

Start instantly and learn at your own schedule.

#### Approx. 12 hours to complete

Suggested: 17 hours/week...

#### English

Subtitles: English

#### 100% online

Start instantly and learn at your own schedule.

#### Approx. 12 hours to complete

Suggested: 17 hours/week...

#### English

Subtitles: English

### Syllabus - What you will learn from this course

Week
1
4 hours to complete

## Working with Sequences

14 videos (Total 41 min), 1 reading, 4 quizzes
14 videos
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
How to send course feedback10m
1 practice exercise
Working with Sequences
15 minutes to complete

## Recurrent Neural Networks

4 videos (Total 15 min), 1 quiz
4 videos
1 practice exercise
Recurrent Neural Networks
4 hours to complete

## Dealing with Longer Sequences

14 videos (Total 62 min), 4 quizzes
14 videos
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 practice exercise
Dealing with Longer Sequences
Week
2
2 hours to complete

## Text Classification

8 videos (Total 35 min), 2 quizzes
8 videos
Lab Intro: Text Classification47s
Lab Solution: Text Classification11m
Python vs Native TensorFlow4m
Demo: Text Classification with Native TensorFlow7m
Summary1m
1 practice exercise
Text Classification
1 hour to complete

## Reusable Embeddings

6 videos (Total 28 min), 2 quizzes
6 videos
Lab Intro: Evaluating a pre-trained embedding from TensorFlow Hub24s
Lab Solution: TensorFlow Hub9m
Using TensorFlow Hub within an estimator1m
1 practice exercise
Reusable Embeddings
3 hours to complete

## Encoder-Decoder Models

10 videos (Total 84 min), 3 quizzes
10 videos
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 practice exercise
Encoder-Decoder Models
14 minutes to complete

## Summary

1 video (Total 4 min), 1 reading
1 video
4.4
25 Reviews

## 50%

started a new career after completing these courses

## 50%

got a tangible career benefit from this course

### Top reviews from Sequence Models for Time Series and Natural Language Processing

By 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!

By JWNov 11th 2018

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

## Instructor

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....

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....