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Home Artificial Intelligence (AI)

How to Perform Sentiment Analysis Using TFX

Adam Smith – Tech Writer & Blogger by Adam Smith – Tech Writer & Blogger
February 27, 2025
in Artificial Intelligence (AI)
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Sentiment Analysis with TFX and Vertex AI Pipelines: A Step-by-Step Tutorial

Sentiment analysis offers significant business benefits, which is why more and more companies are implementing it. If you’re wondering how you can run sentiment analysis using TensorFlow Extended, we have something for you. We’ve created a free step-by-step walkthrough on how to apply BERT to sentiment analysis using TFX and Vertex AI pipelines.

TFX — an Underrated Google Tool

What do you know about TensorFlow Extended (TFX)? The tool offers a well-structured set of Google’s best MLOps practices. It also comes with a set of Google Cloud Platform-targeted components, which are like drop-in replacements for standard TFX components that enable users to leverage the distributed training and serving capabilities of GCP. You can use the library to create Machine Learning pipelines in a clear, declarative way. And the main advantage of the setup is that, for the most part, there’s no code to write to get a pipeline going (except, of course, the feature engineering and modeling code).

A Step-by-Step Tutorial for Running Sentiment Analysis with TFX

We could see the potential of the TFX platform from the outset, but we decided to modify it, running practical research into how to apply the tool to Machine Learning in production. To do this, we decided to pick:

  • Sentiment analysis as the problem
  • BERT as the solution
  • TFX as the tool
  • Vertex AI as the runtime

We chose sentiment analysis as it’s a classic, easy-to-understand Machine Learning problem with a wide range of applications, especially in the retail industry. Similarly, BERT is a widely recognized NLP model that’s also used in retail.

The Step-by-Step Walkthrough

In essence, the step-by-step walkthrough shows you how to:

  • Create a sentiment analysis ML model using ready-made components (BERT)
  • Create an end-to-end MLOps pipeline for training, evaluating, and deploying the model using TFX
  • Deploy the pipeline to Vertex AI Pipelines
  • Preview the key pipeline artifacts

The course also includes open-source code for the entire pipeline and helper library, ready for you to use as templates in your own project. Sound interesting?

Read the Course Online or Download the Free PDF

Click here to read the course online or download the free PDF.

Conclusion

In this article, we have discussed the importance of sentiment analysis and how it can be implemented using TFX and Vertex AI pipelines. We have also provided a step-by-step walkthrough on how to apply BERT to sentiment analysis using TFX and Vertex AI pipelines.

FAQs

Q: What is TFX?
A: TFX is a well-structured set of Google’s best MLOps practices.

Q: What is Vertex AI?
A: Vertex AI is a Google Cloud Platform service for machine learning.

Q: What is BERT?
A: BERT is a widely recognized NLP model.

Q: What is sentiment analysis?
A: Sentiment analysis is an NLP technique used to determine the sentiment or emotional tone of a given text.

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Adam Smith – Tech Writer & Blogger

Adam Smith – Tech Writer & Blogger

Adam Smith is a passionate technology writer with a keen interest in emerging trends, gadgets, and software innovations. With over five years of experience in tech journalism, he has contributed insightful articles to leading tech blogs and online publications. His expertise covers a wide range of topics, including artificial intelligence, cybersecurity, mobile technology, and the latest advancements in consumer electronics. Adam excels in breaking down complex technical concepts into engaging and easy-to-understand content for a diverse audience. Beyond writing, he enjoys testing new gadgets, reviewing software, and staying up to date with the ever-evolving tech industry. His goal is to inform and inspire readers with in-depth analysis and practical insights into the digital world.

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