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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

This ability to understand long-range dependencies helps transformers better understand the context of words and achieve superior performance in natural language processing tasks. As I write this, the bert-base-uncasedmodel on HuggingFace has been downloaded over 53 million times in the last month alone!

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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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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.

OpenAI 147
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Ivan Crewkov CEO & Co-Founder of Buddy AI – Interview Series

Unite.AI

Since its launch in 2020, the Buddy app has won several awards and topped the charts in the App Store's Kids and Education category with over 36M downloads worldwide. We decided that Buddy would be a multimodal AI tutor – an animated pedagogical agent capable of voice recognition and natural language processing.

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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.

NLP 89
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Fireworks AI Open Sources FireLLaVA: A Commercially-Usable Version of the LLaVA Model Leveraging Only OSS Models for Data Generation and Training

Marktechpost

A variety of Large Language Models (LLMs) have demonstrated their capabilities in recent times. With the constantly advancing fields of Artificial Intelligence (AI), Natural Language Processing (NLP), and Natural Language Generation (NLG), these models have evolved and have stepped into almost every industry.