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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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Summary

BQML is a powerful tool for data scientists and analysts who want to train ML models with ease while using a low-code option to build and deploy models in GCP. With BQML, users can leverage the power of BigQuery to quickly and easily create models without needing to write complex code.

In this chapter, we explored the features and benefits of BQML. We saw how it provides a simple and intuitive interface for training models using SQL queries. We also explored some of the key features of BQML, including the ability to perform data preprocessing and feature engineering directly within BigQuery, as well as the ability to evaluate model performance through native evaluation functions.

One of the key advantages of BQML is its integration with BigQuery, which makes it easy to scale and manage large datasets. This makes it a great option for companies and organizations that are dealing with massive amounts of data and need to quickly build and deploy models.

Another advantage...

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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