Remove Auto-classification Remove Categorization Remove Natural Language Processing
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An Overview of the Top Text Annotation Tools For Natural Language Processing

John Snow Labs

Therefore, the data needs to be properly labeled/categorized for a particular use case. In this article, we will discuss the top Text Annotation tools for Natural Language Processing along with their characteristic features. The model must be taught to identify specific entities to make accurate predictions.

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LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

Unite.AI

Second, the White-Box Preset implements simple interpretable algorithms such as Logistic Regression instead of WoE or Weight of Evidence encoding and discretized features to solve binary classification tasks on tabular data. In the situation where there is a single task with a small dataset, the user can manually specify each feature type.

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

Becoming Human

A typical application of GNN is node classification. GNNs are a hybrid of an information diffusion mechanism and neural networks that are used to process data, representing a set of transition functions and a set of output functions. Graph Classification: The goal here is to categorize the entire graph into various categories.

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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. Custom classification is a two-step process.

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How Pixability uses foundation models to accelerate NLP application development by months

Snorkel AI

To help brands maximize their reach, they need to constantly and accurately categorize billions of YouTube videos. Using Snorkel Flow, Pixability leveraged foundation models to build small, deployable classification models capable of categorizing videos across more than 600 different classes with 90% accuracy in just a few weeks.

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How to Use Hugging Face Pipelines?

Towards AI

Hugging Face is a platform that provides pre-trained language models for NLP tasks such as text classification, sentiment analysis, and more. The NLP tasks we’ll cover are text classification, named entity recognition, question answering, and text generation. The pipeline we’re going to talk about now is zero-hit classification.

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Build an image-to-text generative AI application using multimodality models on Amazon SageMaker

AWS Machine Learning Blog

For instance, in ecommerce, image-to-text can automate product categorization based on images, enhancing search efficiency and accuracy. More recently, there has been increasing attention in the development of multimodality models, which are capable of processing and generating content across different modalities.