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You're reading from  The Definitive Guide to Google Vertex AI

Product typeBook
Published inDec 2023
PublisherPackt
ISBN-139781801815260
Edition1st Edition
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Authors (2):
Jasmeet Bhatia
Jasmeet Bhatia
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Jasmeet Bhatia

Jasmeet is a Machine Learning Architect with over 8 years of experience in Data Science and Machine Learning Engineering at Google and Microsoft, and overall has 17 years of experience in Product Engineering and Technology consulting at Deloitte, Disney, and Motorola. He has been involved in building technology solutions that focus on solving complex business problems by utilizing information and data assets. He has built high performing engineering teams, designed and built global scale AI/Machine Learning, Data Science, and Advanced analytics solutions for image recognition, natural language processing, sentiment analysis, and personalization.
Read more about Jasmeet Bhatia

Kartik Chaudhary
Kartik Chaudhary
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Kartik Chaudhary

​Kartik is an Artificial Intelligence and Machine Learning professional with 6+ years of industry experience in developing and architecting large scale AI/ML solutions using the technological advancements in the field of Machine Learning, Deep Learning, Computer Vision and Natural Language Processing. Kartik has filed 9 patents at the intersection of Machine Learning, Healthcare, and Operations. Kartik loves sharing knowledge, blogging, travel, and photography.
Read more about Kartik Chaudhary

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Generating predictions

Once the model deployment is complete, you will see the endpoint listed in the DEPLOY & TEST tab. Underneath that, there will be a Test your model table, listing all feature values required to generate predictions. Fields will already have starting values based on the data used for AutoML training, but you can type in different values and click Predict to generate predictions.

Figure 5.21 – Testing a deployed model

Figure 5.21 – Testing a deployed model

Once the model churns through the provided feature values, it will return the confidence score associated with each label. The one with the highest confidence score is the predicted label.

Figure 5.22 – The prediction result

Figure 5.22 – The prediction result

Now let’s look at the options available to developers to use the Vertex AI models programmatically.

Generating predictions programmatically

To access the Vertex AI prediction service, you can work with the Vertex AI SDK for Python, or client...

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The Definitive Guide to Google Vertex AI
Published in: Dec 2023Publisher: PacktISBN-13: 9781801815260

Authors (2)

author image
Jasmeet Bhatia

Jasmeet is a Machine Learning Architect with over 8 years of experience in Data Science and Machine Learning Engineering at Google and Microsoft, and overall has 17 years of experience in Product Engineering and Technology consulting at Deloitte, Disney, and Motorola. He has been involved in building technology solutions that focus on solving complex business problems by utilizing information and data assets. He has built high performing engineering teams, designed and built global scale AI/Machine Learning, Data Science, and Advanced analytics solutions for image recognition, natural language processing, sentiment analysis, and personalization.
Read more about Jasmeet Bhatia

author image
Kartik Chaudhary

​Kartik is an Artificial Intelligence and Machine Learning professional with 6+ years of industry experience in developing and architecting large scale AI/ML solutions using the technological advancements in the field of Machine Learning, Deep Learning, Computer Vision and Natural Language Processing. Kartik has filed 9 patents at the intersection of Machine Learning, Healthcare, and Operations. Kartik loves sharing knowledge, blogging, travel, and photography.
Read more about Kartik Chaudhary