Youtor
Creating Vector Embeddings TensorFlow universalsentenceencoder and Nodejs
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=BGPbYK71AXc
Learn how to build a movie recommender with TensorFlow, Postgres, PGVector, Javascript Next.js. This is a series of videos where we build a project together step by step. Check the complete playlist here - • TensorFlow, Postgres, PGVector Next... . • In this chapter you’ll learn how to use TensorFlow universal-sentence-encoder to create vector search embeddings in Node.js with Javascript. By following the steps in this video you’ll create a script that loads a model, takes a movie plot example and encodes it into a vector embedding. • You can find helpful links and code snippets in this accompanying article - https://aiven.io/developer/building-a.... • Register with Aiven to host Postgres for free and get extra credits: https://go.aiven.io/get-pgvector • Chapters: • 00:00 About the dataset that we'll use • 00:28 Where to find all links and the dataset • 01:54 How vector search works • 02:47 How to create embeddings using TensorFlow model • 03:36 Installing libraries • 04:50 Writing code to create a vector from a single movie description • 07:58 Running the code • 08:48 Next steps • • ABOUT AIVEN • Aiven’s cloud data platform helps your business reach its highest potential by making your data work for you. • It provides fully managed open source data infrastructure on all major clouds, helping developers focus on what they do best: innovate and create without worrying about the limitations of technology. • We like to think that Aiven is not only a cloud data platform but also an extension of your team. We are dedicated to helping you to succeed by removing barriers and finding the right solutions – with the help of the best data technology there is. • Sign up for a free Aiven account: https://go.aiven.io/youtube-signup • CONNECT WITH US • Website: http://aiven.io • LinkedIn: / aiven • GitHub: https://github.com/aiven • Twitter: / aiven_io
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