Remove Auto-complete Remove Categorization Remove NLP
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Beyond ChatGPT; AI Agent: A New World of Workers

Unite.AI

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape.

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Making Sense of the Mess: LLMs Role in Unstructured Data Extraction

Unite.AI

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text.

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How to Use Hugging Face Pipelines?

Towards AI

A practical guide on how to perform NLP tasks with Hugging Face Pipelines Image by Canva With the libraries developed recently, it has become easier to perform deep learning analysis. Hugging Face is a platform that provides pre-trained language models for NLP tasks such as text classification, sentiment analysis, and more.

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Understanding Graph Neural Network with hands-on example| Part-1

Becoming Human

Graph Classification: The goal here is to categorize the entire graph into various categories. The simplest GCN has only three different operators: Graph convolution Linear layer Nonlinear activation In most cases, the operations are completed in this order. In order to create a complete GCN, we can combine one or more layers.

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Use custom metadata created by Amazon Comprehend to intelligently process insurance claims using Amazon Kendra

AWS Machine Learning Blog

The custom metadata helps organizations and enterprises categorize information in their preferred way. The insurance provider receives payout claims from the beneficiary’s attorney for different insurance types, such as home, auto, and life insurance. For example, metadata can be used for filtering and searching. append(e["Text"].upper())

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Build well-architected IDP solutions with a custom lens – Part 5: Cost optimization

AWS Machine Learning Blog

An intelligent document processing (IDP) project usually combines optical character recognition (OCR) and natural language processing (NLP) to read and understand a document and extract specific terms or words. If you’re not actively using the endpoint for an extended period, you should set up an auto scaling policy to reduce your costs.

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Introducing spaCy v3.1

Explosion

SpanCategorizer for predicting arbitrary and overlapping spans A common task in applied NLP is extracting spans of texts from documents, including longer phrases or nested expressions. skweak Toolkit for weak supervision applied to NLP tasks ? en_ner_fashion./output output --build wheel cd. spaCy v3.1 : What’s new in v3.1

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