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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

Flipboard

By combining the capabilities of LLM function calling and Pydantic data models, you can dynamically extract metadata from user queries. These steps will guide you through deleting your knowledge base, vector database, AWS Identity and Access Management (IAM) roles, and sample datasets, making sure that you don’t incur unexpected costs.

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Announcing general availability of Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune Analytics

AWS Machine Learning Blog

This new capability integrates the power of graph data modeling with advanced natural language processing (NLP). For Embeddings model , choose an embeddings model, such as Amazon Titan Text Embeddings v2. For Vector database , select Quick create a new vector store and then select Amazon Neptune Analytics (GraphRAG).

Analytics 123
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5 Recent Data Science and AI Webinars You Need to See

ODSC - Open Data Science

Each month, ODSC has a few insightful webinars that touch on a range of issues that are important in the data science world, from use cases of machine learning models, to new techniques/frameworks, and more. So here’s a summary of a few recent webinars that you’ll want to watch. Watch on-demand here.

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Using anti-requirements to find system boundaries

Hacker News

1 But inevitably, starting a new project involves lots of meetings with business stakeholders to hash out initial requirements and canonical data models. For example, you might need the data to be denormalized for performance, or the warehouse data might exist on a physically different system that can’t participate in a database join.

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Cassandra vs MongoDB

Pickl AI

Summary: Apache Cassandra and MongoDB are leading NoSQL databases with unique strengths. Introduction In the realm of database management systems, two prominent players have emerged in the NoSQL landscape: Apache Cassandra and MongoDB. Flexible Data Model: Supports a wide variety of data formats and allows for dynamic schema changes.

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Who is a BI Developer: Role, Responsibilities & Skills

Pickl AI

It is the process of converting raw data into relevant and practical knowledge to help evaluate the performance of businesses, discover trends, and make well-informed choices. Data gathering, data integration, data modelling, analysis of information, and data visualization are all part of intelligence for businesses.

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Building and Scaling Gen AI Applications with Simplicity, Performance and Risk Mitigation in Mind Using Iguazio (acquired by McKinsey) and MongoDB

Iguazio

MongoDB for end-to-end AI data management MongoDB Atlas , an integrated suite of data services centered around a multi-cloud NoSQL database, enables developers to unify operational, analytical, and AI data services to streamline building AI-enriched applications.

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