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Vector Search

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May 1, 2024 4 minute read

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Vector Search is a technique for finding and retrieving similar data points in high-dimensional vector spaces. It is commonly used in a variety of applications, including image and video retrieval, natural language processing, and recommender systems.

How Vector Search Works

Vector search works by representing data points as vectors in a high-dimensional space. These vectors are then indexed and stored in a data structure that enables efficient searching and retrieval. When a query vector is presented, the search engine computes the similarity between the query vector and all the indexed vectors. The results are then ranked based on the similarity scores, and the top-ranked results are returned to the user.

Benefits of Vector Search

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Path to Vector Search

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We've curated 21 courses to help you on your path to Vector Search. Use these to develop your skills, build background knowledge, and put what you learn to practice.

Sorted from most relevant to least relevant:

Getting Started with Vector Search and Embeddings

Getting Started with Vector Search and Embeddings

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Vector Search and Embeddings

Vector Search and Embeddings

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Vector Search and Embeddings

Vector Search and Embeddings

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Crea embeddings, búsqueda de vectores y RAG con BigQuery

Crea embeddings, búsqueda de vectores y RAG con BigQuery

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Vector Search and Embeddings - 한국어

Vector Search and Embeddings - 한국어

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Criar embeddings, pesquisa vetorial e RAG com o BigQuery

Criar embeddings, pesquisa vetorial e RAG com o BigQuery

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Créer des embeddings et utiliser la recherche vectorielle et le RAG avec BigQuery

Créer des embeddings et utiliser la recherche vectorielle...

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Create Embeddings, Vector Search, and RAG with BigQuery

Create Embeddings, Vector Search, and RAG with BigQuery

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Select a Google Cloud Database for Your Applications

Select a Google Cloud Database for Your Applications

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Introduction to Milvus (Vector Database) Using Python

Introduction to Milvus (Vector Database) Using Python

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Vector Search with NoSQL Databases using MongoDB & Cassandra

Vector Search with NoSQL Databases using MongoDB &...

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Vector Search and Embeddings - 日本語版

Vector Search and Embeddings - 日本語版

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Vector Search and Embeddings - Français

Vector Search and Embeddings - Français

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Vector Search and Embeddings - Português Brasileiro

Vector Search and Embeddings - Português Brasileiro

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Vector Search and Embeddings - Deutsch

Vector Search and Embeddings - Deutsch

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Vector Search with Relational Databases using PostgreSQL

Vector Search with Relational Databases using PostgreSQL

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Vector Search and Embeddings - Español

Vector Search and Embeddings - Español

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Vector Search and Embeddings - 繁體中文

Vector Search and Embeddings - 繁體中文

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Prompt Compression and Query Optimization

Prompt Compression and Query Optimization

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Vector Search and Embeddings - 简体中文

Vector Search and Embeddings - 简体中文

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Vector Search and Embeddings - Bahasa Indonesia

Vector Search and Embeddings - Bahasa Indonesia

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Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Vector Search.

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Cover image

Natural Language Processing with Python

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A comprehensive guide to natural language processing in Python, including chapters on vector representations of text and their use in natural language processing tasks.

Natural Language Processing with Python: Analyzing...

(中文) Python Natural Language Processing(Chinese Edition)

Natural Language Processing with Python: Analyzing...

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Python Machine Learning

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A comprehensive introduction to deep learning for natural language processing, including a chapter on word embeddings and their use in vector search.

Machine Learning with PyTorch and Scikit-Learn:...

Machine Learning with PyTorch and Scikit-Learn:...

Python Machine Learning: Machine Learning and Deep...

Python Machine Learning - Second Edition: Machine...

(Italiano) Machine Learning con Python - Nuova edizione:...

(Deutsch) Machine Learning mit Python und Keras, TensorFlow 2...

(Español) Machine Learning con PyTorch y Scikit-Learn:...

(Español) Python Machine Learning

Relevant careers

Application Developer

Machine Learning Engineer

Software Engineer

Information Retrieval Specialist

Natural Language Processing Engineer

Computer Vision Engineer

Related topics

Machine Learning

Natural Language Processing

Computer Vision

Software Engineering

Information Retrieval

Cloud Computing

Artificial Intelligence

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