Vector Search for Practitioners with Elastic

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Introduction to Vectors and Embeddings

In this first chapter, we will dive into the fascinating world of embeddings, or vectors, and their diverse applications across various domains. We’ll introduce the concept of embeddings, which help represent complex data and enable powerful machine learning (ML) models to analyze and process that data. You’ll learn about the roles of supervised and unsupervised learning in creating embeddings and the challenges addressed by vectors. Moreover, we’ll discuss examples illustrating the broad applications of vector representation in different fields. We’ll also introduce you to the ecosystem of tools and platforms that enhance the developer experience when working with vector search, including Hugging Face ...