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Natural Language Processing (NLP) Concepts With NLTK

Heartbeat

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk on Unsplash At its core, the discipline of Natural Language Processing (NLP) tries to make the human language “palatable” to computers.

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Natural Language Processing with R

Heartbeat

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

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A Quick Recap of Natural Language Processing

Mlearning.ai

Photo by Eugene Zhyvchik on Unsplash I wanted to share a short perspective of the radical evolution we have seen in NLP. I’ve been working on NLP problems since word2vec was released, and it has been remarkable to see how quickly the models, problems, and applications have evolved. In other words, it was and is a pretty big deal.

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AI News Weekly - Issue #383: New York Daily News, Chicago Tribune, and others sue OpenAI and Microsoft - May 2nd 2024

AI Weekly

Download our GenAI Planning Roadmap to get your project off to the right start! Download now] rws.com In The News Meet Amazon Q, the AI assistant that generates apps for you Amazon released its AI-powered assistant for developers and businesses in general availability, new free courses, and a new Amazon Q capability in preview.

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Accelerate NLP inference with ONNX Runtime on AWS Graviton processors

AWS Machine Learning Blog

Bfloat16 accelerated SGEMM kernels and int8 MMLA accelerated Quantized GEMM (QGEMM) kernels in ONNX have improved inference performance by up to 65% for fp32 inference and up to 30% for int8 quantized inference for several natural language processing (NLP) models on AWS Graviton3-based Amazon Elastic Compute Cloud (Amazon EC2) instances.

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Training Relations Models in NLP Lab 5.7

John Snow Labs

marks a significant milestone in the realm of natural language processing with the introduction of advanced Relation Extraction (RE) model training features. Training Relations Extraction (RE) Model We are excited to announce that NLP Lab 5.7 Detailed descriptions of all new features and improvements are provided below.

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Boost Your NLP Results with Spark NLP Stemming and Lemmatizing Techniques

John Snow Labs

Stemming and lemmatization are vital techniques in NLP for transforming words into their base or root forms. Spark NLP provides powerful capabilities for stemming and lemmatization, enabling researchers and practitioners to improve the quality of their NLP tasks and extract more meaningful insights from text data.

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