This course is an introduction to sequence models and their applications, including an overview of sequence model architectures and how to handle inputs of variable length.
This course is part of the Advanced Machine Learning on Google Cloud Specialization
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Course 4 of 5 in the
Advanced Level
Approx. 13 hours to complete
English
Subtitles: English
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 4 of 5 in the
Advanced Level
Approx. 13 hours to complete
English
Subtitles: English
Offered by
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.
Syllabus - What you will learn from this course
18 minutes to complete
Course introduction
This module addresses the reasons to learn NLP from Google and provides an overview of the course structure and goals.
18 minutes to complete
2 videos (Total 8 min), 1 reading
3 hours to complete
NLP on Google Cloud
This module introduces the NLP architecture on Google Cloud. It explores the NLP history, the NLP APIs such as the Dialogflow API, and the NLP solutions such as Contact Center AI and Document AI.
3 hours to complete
9 videos (Total 39 min), 1 reading, 2 quizzes
3 hours to complete
NLP with Vertex AI
This module explores AutoML and custom training, which are the two options to develop an NLP project with Vertex AI. Additionally, the module introduces an end-to-end NLP workflow and provides a hands-on lab to apply the workflow to solve a task of text classification with AutoML.
3 hours to complete
8 videos (Total 23 min), 1 reading, 2 quizzes
2 hours to complete
Text representatation
This module describes the process to prepare text data in NLP and introduces the major categories of text representation techniques.
2 hours to complete
8 videos (Total 36 min), 1 reading, 2 quizzes
3 hours to complete
NLP models
This module describes different NLP models including ANN, DNN, RNN, LSTM, and GRU. It also introduces the benefits and disadvantages of each model.
3 hours to complete
9 videos (Total 48 min), 1 reading, 2 quizzes
Reviews
- 5 stars63.23%
- 4 stars22.68%
- 3 stars8.19%
- 2 stars2.94%
- 1 star2.94%
TOP REVIEWS FROM NATURAL LANGUAGE PROCESSING ON GOOGLE CLOUD
by ASAug 16, 2019
I like it because it is very relevant to my work. The dialogflow part is a bit weak. I am not sure if it is the product or the course.
by MDFeb 2, 2019
Very good.The explanation of the RNN was very good but the tensor2tensor was very hard.
by DDJan 20, 2020
Felt somewhat advanced learning, which made tough to complete intime
by NDFeb 28, 2020
I have only one remark, please improve lesson regarding NLP by includin model build etc.
Otherwise course is excellent and was helpful for me
About the Advanced Machine Learning on Google Cloud Specialization
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.
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