Remove Data Extraction Remove NLP Remove Prompt Engineering
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10 Best Prompt Engineering Courses

Unite.AI

In the ever-evolving landscape of artificial intelligence, the art of prompt engineering has emerged as a pivotal skill set for professionals and enthusiasts alike. Prompt engineering, essentially, is the craft of designing inputs that guide these AI systems to produce the most accurate, relevant, and creative outputs.

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Information extraction with LLMs using Amazon SageMaker JumpStart

AWS Machine Learning Blog

This post walks through examples of building information extraction use cases by combining LLMs with prompt engineering and frameworks such as LangChain. We also examine the uplift from fine-tuning an LLM for a specific extractive task. In this example, you explicitly set the instance type to ml.g5.48xlarge.

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Enterprise LLM APIs: Top Choices for Powering LLM Applications in 2024

Unite.AI

Data Extraction & Analysis : Summarizing large reports or extracting key insights from datasets using GPT-4’s advanced reasoning abilities. Cohere Cohere specializes in natural language processing (NLP) and provides scalable solutions for enterprises, enabling secure and private data handling.

LLM 246
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How to Prompt on OpenAI’s o1 Models and What’s Different From GPT-4

Marktechpost

One of the key features of the o1 models is their ability to work efficiently across different domains, including natural language processing (NLP), data extraction, summarization, and even code generation.

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The Patterns in Generative AI Lifecycles

Mlearning.ai

Prompt, In-context Learning and Chaining Step 1 You pick a model, give it a prompt, get a response, evaluate the response, and re-prompt if needed until you get the desired outcome. In-context learning is a prompt engineering approach where language models learn tasks from a few natural language examples and try to perform them.

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Intelligent Document Processing with AWS AI Services and Amazon Bedrock

ODSC - Open Data Science

We use Amazon Textract’s document extraction abilities with LangChain to get the text from the document and then use prompt engineering to identify the possible document category. LangChain uses Amazon Textract’s DetectDocumentText API for extracting text from printed, scanned, or handwritten documents.

IDP 98
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Bloomberg’s Gideon Mann on the power of domain specialist LLMs

Snorkel AI

What are the key advantages that it offers for financial NLP tasks? Gideon Mann: To your point about data-centric AI and the commoditization of LLMs, when I look at what’s come out of open-source and academia, and the people working on LLMs, there has been amazing progress in making these models easier to use and train.