Natural Language Processing on Google Cloud

Course Feature
  • Cost
    Free
  • Provider
    Coursera
  • Certificate
    Paid Certification
  • Language
    English
  • Start Date
    17th Jul, 2023
  • Learners
    No Information
  • Duration
    No Information
  • Instructor
    Google Cloud Training
Next Course
2.0
0 Ratings
This course introduces the products and solutions to solve Natural Language Processing (NLP) problems on Google Cloud. It explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow. Participants will learn to recognize the NLP products and the solutions on Google Cloud, create an end-to-end NLP workflow by using AutoML with Vertex AI, build different NLP models including DNN, RNN, LSTM, and GRU by using TensorFlow, recognize advanced NLP models such as encoder-decoder, attention mechanism, transformers, and BERT, understand transfer learning and apply pre-trained models to solve NLP problems. Basic SQL, familiarity with Python and TensorFlow are the prerequisites for this course.
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Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [May 30th, 2023]

What skills and knowledge will you acquire during this course?
This course on Natural Language Processing on Google Cloud provides users with a comprehensive introduction to the products and solutions to solve NLP problems on Google Cloud. Through this course, users will acquire skills such as building different NLP models, recognizing advanced NLP models, understanding transfer learning, and applying pre-trained models to solve NLP problems. Additionally, users will gain knowledge in related topics such as basic SQL, Python, and TensorFlow. With the knowledge and skills acquired from this course, users can explore possible development paths in their career or education related to NLP.

How does this course contribute to professional growth?
This course on Natural Language Processing on Google Cloud provides a comprehensive introduction to the products and solutions to solve NLP problems on Google Cloud. It also provides users with the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow. With the knowledge gained from this course, users can explore possible development paths in their career or education, such as building different NLP models, recognizing advanced NLP models, understanding transfer learning, and applying pre-trained models to solve NLP problems. Additionally, users can also find related learning suggestions to further their knowledge in the field of NLP. This course can contribute to professional growth by providing users with the necessary skills and knowledge to develop NLP projects and explore related topics. It can also help users to gain a better understanding of the field of NLP and the tools and techniques used to develop projects.

Is this course suitable for preparing further education?
This course on Natural Language Processing on Google Cloud provides a comprehensive introduction to the products and solutions to solve NLP problems on Google Cloud, as well as the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow. With the knowledge gained from this course, users can explore possible development paths in their career or education, such as building different NLP models, recognizing advanced NLP models, understanding transfer learning, and applying pre-trained models to solve NLP problems. Additionally, users can also find related learning suggestions to further their knowledge in the field of NLP, such as learning basic SQL, becoming familiar with Python and TensorFlow, and exploring other NLP-related topics. Therefore, this course is suitable for preparing further education in the field of Natural Language Processing.

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Pros & Cons
  • Good presentation of materials.
  • Great technology and teachers.
  • Excellent lectures and broad subject area.
  • Poor assignments on Qwik labs.
  • Synchronization between videos and labs is extreme.
  • Library mismatch led to errors.
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