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How to Build NLP Applications with Hugging Face?

Analytics Vidhya

This article will delve into Hugging Face’s capabilities for building NLP applications, covering key services such as models, datasets, and open-source libraries. Whether you are a beginner or an experienced developer, Hugging Face offers versatile tools to […] The post How to Build NLP Applications with Hugging Face?

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Introduction to Natural Language Processing [Free NLP Course]

Analytics Vidhya

Introduction Natural Language Processing (NLP) has recently received much attention in computationally representing and analyzing human speech. But what if you want to learn NLP without spending money?

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A Comprehensive NLP Learning Path 2024

Analytics Vidhya

Introduction The year 2023 witnessed groundbreaking advancements in Natural Language Processing (NLP) with the rise of powerful language models like Bard, Gemini, and ChatGPT.

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Exploring Diffusion Models in NLP Beyond GANs and VAEs

Analytics Vidhya

Introduction Diffusion Models have gained significant attention recently, particularly in Natural Language Processing (NLP). Based on the concept of diffusing noise through data, these models have shown remarkable capabilities in various NLP tasks.

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Enhancing NLP Pipelines with spaCy

Analytics Vidhya

Introduction spaCy is a Python library for Natural Language Processing (NLP). NLP pipelines with spaCy are free and open source. If you work with a lot of text, you’ll […] The post Enhancing NLP Pipelines with spaCy appeared first on Analytics Vidhya.

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Sentiment Analysis with NLP

Analytics Vidhya

That is where NLP comes into the picture. In simple terms, NLP helps to teach computers to […]. The post Sentiment Analysis with NLP appeared first on Analytics Vidhya. Introduction In today’s world, we know that we interact greatly with our smart devices.

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Common Flaws in NLP Evaluation Experiments

Ehud Reiter

The ReproHum project (where I am working with Anya Belz (PI) and Craig Thomson (RF) as well as many partner labs) is looking at the reproducibility of human evaluations in NLP. So User interface problems : Very few NLP papers give enough information about UIs to enable reviewers to check these for problems. Especially

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