The Vertex AI Text-Embeddings API enhances the process of generating text embeddings. These text embeddings, which are numerical representations of text, play a pivotal role in many tasks involving the identification of similar items, like Google searches, online shopping recommendations, and personalized music suggestions.
Understanding and Applying Text Embeddings
Understanding and Applying Text Embeddings
Instructors: Andrew Ng
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Build in-demand job skills with step-by-step instructions
4.8
(56 reviews)
Beginner level
Recommended experience
1 hour
Learn at your own pace
Hands-on learning
What you'll learn
Apply text embeddings for tasks such as classification, clustering, and outlier detection.
Modify the text generation behavior of an LLM by adjusting the parameters temperature, top-k, and top-p.
Apply the open source ScaNN (Scalable Nearest Neighbors) library for efficient semantic search.
Skills you'll practice
Details to know
Taught in English
No downloads or installation required
Only available on desktop
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About this project
Instructors
Instructor ratings
5.0 (8 ratings)Offered by
How you'll learn
Hands-on, project-based learning
Practice new skills by completing job-related tasks with step-by-step instructions.
No downloads or installation required
Access the tools and resources you need in a cloud environment.
Available only on desktop
This project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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4.8
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ZG
5
Reviewed on Sep 3, 2024
thanks for your effort dear Andrew NG for teaching
OT
5
Reviewed on Feb 22, 2024
a simple yet powerfull courses to understand how to do semantic search and using vertex ai
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