This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.
Natural Language Processing on Google Cloud
Natural Language Processing on Google Cloud
This course is part of Advanced Machine Learning on Google Cloud Specialization
Instructor: Google Cloud Training
21,516 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.4
(531 reviews)
Advanced level
Designed for those already in the industry
Flexible schedule
Approx. 10 hours
Learn at your own pace
77%
Most learners liked this course
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Shareable certificate
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Assessments
5 assignments
Taught in English
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This course is part of the Advanced Machine Learning on Google Cloud 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
This module addresses the reasons to learn NLP from Google and provides an overview of the course structure and goals.
What's included
2 videos1 reading
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.
What's included
9 videos1 reading1 assignment1 app item
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.
What's included
7 videos1 reading1 assignment
This module describes the process to prepare text data in NLP and introduces the major categories of text representation techniques.
What's included
8 videos1 reading1 assignment1 app item
This module describes different NLP models including ANN, DNN, RNN, LSTM, and GRU. It also introduces the benefits and disadvantages of each model.
What's included
9 videos1 reading1 assignment1 app item
This module introduces the state-of-the-art technologies and models in NLP: encoder-decoder, attention mechanism, transformers, BERT, and large language models.
What's included
8 videos1 reading1 assignment1 app item
This module reviews the topics covered in the course and provides additional resources for further learning.
What's included
1 video
Instructor
Instructor ratings
4.7 (27 ratings)Offered by
Recommended if you're interested in Machine Learning
DeepLearning.AI
Google Cloud
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4.4
531 reviews
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Showing 3 of 531
MN
4
Reviewed on Jun 9, 2019
Very helpful but needs more in depth detail how attention works, how encoder/decoder trains and makes predictions
YC
5
Reviewed on Jul 13, 2020
This course is short and sweet, and covers many helpful usecases of GCP tools related to the course topic.
MD
5
Reviewed on Feb 2, 2019
Very good.The explanation of the RNN was very good but the tensor2tensor was very hard.
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.