AWS Machine Learning Blog

AUGUST 9, 2024

Deltek is continuously working on enhancing this solution to better align it with their specific requirements, such as supporting file formats beyond PDF and implementing more cost-effective approaches for their data ingestion pipeline. The first step is data ingestion, as shown in the following diagram. What is RAG?

Data Ingestion 124

Data Ingestion Metadata LLM Generative AI 124

AWS Machine Learning Blog

AUGUST 8, 2024

This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock. Twilio’s use case Twilio wanted to provide an AI assistant to help their data analysts find data in their data lake.

Metadata 117

Metadata LLM Prompt Engineering Prompt Engineer 117

AWS Machine Learning Blog

OCTOBER 2, 2024

It’s a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like Anthropic, Cohere, Meta, Mistral AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Generative AI 118

Generative AI Data Ingestion AI AI 118

The MLOps Blog

JUNE 27, 2023

Core features of end-to-end MLOps platforms End-to-end MLOps platforms combine a wide range of essential capabilities and tools, which should include: Data management and preprocessing : Provide capabilities for data ingestion, storage, and preprocessing, allowing you to efficiently manage and prepare data for training and evaluation.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

John Snow Labs

FEBRUARY 18, 2025

This talk will explore a new capability that transforms diverse clinical data (EHR, FHIR, notes, and PDFs) into a unified patient timeline, enabling natural language question answering.

Generative AI 52

Generative AI Data Ingestion Metadata Automation 52

ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: MLOps Fundamentals LLM Deployment & Monitoring Cloud Infrastructure forLLMs Observability & Cost Management Operationalizing Local LLMs Responsibly Who Should Attend: MLOps Engineers, Data Scientists, and AI Developers responsible for deploying AIsystems.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

ODSC - Open Data Science

SEPTEMBER 17, 2024

This talk will also cover the implementation of the RAISE framework, which stands for Responsible AI Security Engineering, designed to provide a step-by-step approach to building secure and resilient AI systems.

LLM 52

LLM Large Language Models Metadata Data Science 52