Pinecone Vector Database in Production
«Pinecone Vector Database in Production» è un corso online di Agenti AI e framework di livello principiante, tenuto da InsightLearn Curated AI su InsightLearn. Il percorso comprende 9 lezioni organizzate in 3 sezioni, per una durata complessiva di 5h 0m. Pinecone serverless: indici, upsert, query, namespace, metadata filter, sparse-dense hybrid. Scaling RAG fino a miliardi di vettori.
- Docente: InsightLearn Curated AI
- Categoria: Agenti AI e framework
- Livello: principiante
- Durata: 5h 0m
- Accesso: gratuito in questa fase di validazione, in cambio di un feedback al termine
- Certificato: certificato di completamento verificabile online
Descrizione del corso
InsightLearn è in fase di sviluppo (work in progress): i contenuti di questa pagina sono pubblicati esclusivamente a fini di verifica e test.
Pinecone serverless: indici, upsert, query, namespace, metadata filter, sparse-dense hybrid. Scaling RAG fino a miliardi di vettori.
Cosa imparerai
- Curated from public resources. Pinecone serverless: indici, upsert, query, namespace, metadata filter, sparse-dense hybrid. Scaling RAG fino a miliardi di vettori.
Programma del corso
- Account + primo indice serverless (10 min)
- Serverless vs pod-based (10 min)
- Dimensioni embeddings + metric (10 min)
- Upsert con metadata (10 min)
- Query + metadata filter (10 min)
- Namespace multi-tenant (10 min)
- Hybrid search (sparse-dense) (10 min)
- Scaling pattern (10 min)
- Backup e disaster recovery (10 min)
Dalle lezioni
Estratto della trascrizione di «Account + primo indice serverless»
Hello and welcome. My name is Juan Luis Polo. I'm an Associate Specialist Solutions Architect at AWS and in this video we're going to present to you how to set up an Amazon OpenSearch Serverless collection and how you can get started with the service. Amazon OpenSearch Serverless is an on-demand auto-scaling configuration for Amazon OpenSearch Service. OpenSearch Serverless makes it easy for you to run large-scale and analytics workloads without having to configure, marnage, or scale an OpenSearch cluster. Serverless is an on-demand auto-scaling configuration for Azure. Serverless also takes care of undifferentiated heavy lifting or of managing indexes and charts while automatically provisioning and scaling the underlying resources to deliver fast data ingestion and query responses. OpenSearch Serverless…
Estratto della trascrizione di «Serverless vs pod-based»
Hello, how are you doing? In this video, I'm going to talk about Pinecone Pods versus Serverless. Have you heard the term pods or serverless in the context of Pinecone? And you're not quite sure you know exactly what this is. Well if so, then watch along with me for the next few minutes and I'll quickly get you up to speed. Okay, let's get started. Pinecone has two infrastructure deployment models. The first is pods. A Pinecone pod is a dedicated set of resources that you re... reserve and manage for your specific use case. A pod consists of compute, memory, and storage capacity that is allocated exclusively for your workload. Pods can scale vertically up or down based…
Estratto della trascrizione di «Dimensioni embeddings + metric»
Recently, vector databases got a lot of fame with companies raising hundreds of millions of dollars to build them and people calling it a new kind of database for the AI era. On the other hand, for many projects it might be an overkill solution and using a traditional database or even just a NumPy and D array might work just fine. But there is no doubt that vector databases are extremely fascinating and allow many great applications, especially when you want to give large language models. like GPT-4 long-term memory. So in this video I will explain in a very beginner-friendly way what vector databases are and how they work. We will go over some use cases for them…
Altri corsi di Agenti AI e framework
- Qdrant e Weaviate: Vector DB Open Source Self-Hosted
- smolagents HuggingFace: Agent Lightweight Code-First
- Vercel AI SDK: Chatbot Multi-Provider in TypeScript
- AutoGen Microsoft: Multi-Agent Conversation Framework
- CrewAI: Orchestrazione Multi-Agent Role-Based
- DSPy Stanford: Programming LLM Pipelines, Non Prompt Engineering
Domande frequenti
Quanto dura il corso Pinecone Vector Database in Production?
Il corso dura 5h 0m in totale, con 9 lezioni suddivise in 3 sezioni, da seguire online al proprio ritmo.
Serve esperienza pregressa?
Il corso è di livello principiante e non indica requisiti specifici di ingresso.
Il corso rilascia un certificato?
Sì: al completamento del corso ricevi un certificato di completamento verificabile online.