Dataconomy

APRIL 21, 2025

Natural language processing (NLP) is a fascinating field at the intersection of computer science and linguistics, enabling machines to interpret and engage with human language. What is natural language processing (NLP)?

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KDnuggets

OCTOBER 21, 2024

Enhance your NLP skills through a variety of resources, including roadmaps, frameworks, courses, tutorials, example code, and projects.

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Natural Language Processing 360

KDnuggets

JANUARY 29, 2024

The post highlights real-world examples of NLP use cases across industries. It also covers NLP's objectives, challenges, and latest research developments.

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Data Science Dojo

NOVEMBER 27, 2024

This guide is invaluable for understanding how LLMs drive innovations across industries, from natural language processing (NLP) to automation. We as humans rely on language to talk to people, but it cannot be used when interacting with a computer system.

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insideBIGDATA

NOVEMBER 18, 2024

From optimizing contract reviews with natural language processing to enabling cross-departmental collaboration and proactive risk assessment, Daniela talks about how AI is transforming contract lifecycle management into a more efficient, accurate, and proactive function within organizations.

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KDnuggets

FEBRUARY 21, 2025

Its perfect for environments with limited processing power and memory. DistilBERT is a smaller, faster version of BERT that performs well with fewer resources.

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Analytics Vidhya

JANUARY 29, 2025

Beam search is a powerful decoding algorithm extensively used in natural language processing (NLP) and machine learning. It is especially important in sequence generation tasks such as text generation, machine translation, and summarization.

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Analytics Vidhya

JANUARY 1, 2025

Deep learning GPU benchmarks has revolutionized the way we solve complex problems, from image recognition to natural language processing.

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Analytics Vidhya

NOVEMBER 20, 2024

Large Language Models like BERT, T5, BART, and DistilBERT are powerful tools in natural language processing where each is designed with unique strengths for specific tasks. Whether it’s summarization, question answering, or other NLP applications. These models vary in their architecture, performance, and efficiency.

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Analytics Vidhya

JANUARY 20, 2025

Since its introduction in 2018, BERT has transformed Natural Language Processing. It performs well in tasks like sentiment analysis, question answering, and language inference. Using bidirectional training and transformer-based self-attention, BERT introduced a new way to understand relationships between words in text.

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insideBIGDATA

FEBRUARY 15, 2023

The transformer architecture, which was introduced in this paper, is now used in a variety of state-of-the-art models in natural language processing and beyond. Transformers are the basis of the large language models (LLMs) we're seeing today. This paper is a major turning point in deep learning research.

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Analytics Vidhya

JANUARY 20, 2025

ModernBERT is an advanced iteration of the original BERT model, meticulously crafted to elevate performance and efficiency in natural language processing (NLP) tasks.

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Analytics Vidhya

NOVEMBER 7, 2022

So, the task of emotion analysis of online texts is crucial in Natural Language Processing. Introduction With the rapid growth of social network platforms, more and more people tend to share their experiences and emotions online. Sometimes, it is also important to know the cause of the observed emotion.

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KDnuggets

MARCH 30, 2023

Work on data analytics, time series, natural language processing, machine learning, and ChatGPT projects to improve your chance of getting hired.

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insideBIGDATA

DECEMBER 22, 2023

In this contributed article, consultant and thought leader Richard Shan, believes that generative AI holds immense potential to transform information technology, offering innovative solutions for content generation, programming assistance, and natural language processing.

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Analytics Vidhya

JUNE 13, 2024

Introduction Large language models (LLMs) have revolutionized natural language processing (NLP), enabling various applications, from conversational assistants to content generation and analysis.

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Analytics Vidhya

JULY 27, 2024

This is where the term frequency-inverse document frequency (TF-IDF) technique in Natural Language Processing (NLP) comes into play. Introduction Understanding the significance of a word in a text is crucial for analyzing and interpreting large volumes of data.

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Analytics Vidhya

SEPTEMBER 18, 2024

Introduction Large Language Models (LLMs) contributed to the progress of Natural Language Processing (NLP), but they also raised some important questions about computational efficiency. These models have become too large, so the training and inference cost is no longer within reasonable limits.

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Analytics Vidhya

MAY 29, 2024

Introduction One of the most important tasks in natural language processing is text summarizing, which reduces long texts to brief summaries while maintaining important information.

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Machine Learning Research at Apple

APRIL 6, 2025

Progress in natural language processing enables more intuitive ways of interacting with technology. For example, many of Apples products and services, including Siri and search, use natural language understanding and generation to enable a fluent and seamless interface experience for users.

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Machine Learning Research at Apple

APRIL 3, 2025

Large Language Models (LLMs) have transformed natural language processing, but face significant challenges in widespread deployment due to their high runtime cost. In this paper, we introduce SeedLM, a novel post-training compression method that uses seeds of a pseudo-random generator to encode and compress model weights.

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Analytics Vidhya

AUGUST 25, 2024

This is the beauty of Amazon Alexa, a smart speaker that is driven by Natural Language Processing and Artificial Intelligence. Introduction Sitting in front of a desktop, away from you, is your own personal assistant, she knows the tone of your voice, answers to your questions and is even one step ahead of you.

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Analytics Vidhya

APRIL 25, 2024

This innovative blog introduces a user-friendly interface where complex tasks are simplified into plain language queries. Explore the fusion of natural language processing and advanced AI models, transforming intricate tasks into straightforward conversations.

Machine Learning 315

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Analytics Vidhya

MAY 17, 2024

Introduction In natural language processing (NLP), sequence-to-sequence (seq2seq) models have emerged as a powerful and versatile neural network architecture.

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databricks

NOVEMBER 26, 2024

Large language models are revolutionizing how we interact with technology by leveraging advanced natural language processing to perform complex tasks. In recent years.

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Analytics Vidhya

APRIL 19, 2024

Introduction Wayve, a leading artificial intelligence company based in the United Kingdom, introduces Lingo-2, a groundbreaking system that harnesses the power of natural language processing. It integrates vision, language, and action to explain and determine driving behavior.

Natural Language Processing 305

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Analytics Vidhya

AUGUST 23, 2024

Introduction Artificial Intelligence has seen remarkable advancements in recent years, particularly in natural language processing. Among the numerous AI language models, two have garnered significant attention: ChatGPT-4 and Llama 3.1.

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Analytics Vidhya

MAY 13, 2024

Introduction Transformers have revolutionized various domains of machine learning, notably in natural language processing (NLP) and computer vision. Their ability to capture long-range dependencies and handle sequential data effectively has made them a staple in every AI researcher and practitioner’s toolbox.

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Analytics Vidhya

MAY 1, 2024

Google’s latest breakthrough in natural language processing (NLP), called Gecko, has been gaining a lot of interest since its launch. Unlike traditional text embedding models, Gecko takes a whole new approach by distilling knowledge from large language models (LLMs).

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Analytics Vidhya

JUNE 16, 2023

Introduction Large Language Models (LLMs) have revolutionized natural language processing, enabling computers to generate human-like text and understand context with unprecedented accuracy. In this article, we shall discuss what will be the future of language models? How LLMs will revolutionise the world?

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Analytics Vidhya

SEPTEMBER 20, 2023

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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Analytics Vidhya

MAY 15, 2024

Their versatility and efficiency stem from their use of the most recent developments in machine learning and natural language processing. AI assistants help increase our productivity by handling activities like coding, email sorting, and meeting scheduling.

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Analytics Vidhya

APRIL 22, 2024

Introduction In natural language processing (NLP), it is important to understand and effectively process sequential data. Before delving into the intricacies of LSTM language translation models, […] The post Language Translation Using LSTM appeared first on Analytics Vidhya.

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Analytics Vidhya

JUNE 6, 2024

This will help the large language models understand English text and generate meaningful full tokens during the generation period. One of the other common tasks in Natural Language Processing is the Sequence Classification Task. […] The post How to Finetune Llama 3 for Sequence Classification?

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Analytics Vidhya

MARCH 30, 2024

Introduction With the advent of Large Language Models (LLMs), they have permeated numerous applications, supplanting smaller transformer models like BERT or Rule Based Models in many Natural Language Processing (NLP) tasks.

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Analytics Vidhya

OCTOBER 19, 2023

Introduction Step into the forefront of language processing! In a realm where language is an essential link between humanity and technology, the strides made in Natural Language Processing have unlocked some extraordinary heights.

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Analytics Vidhya

SEPTEMBER 15, 2024

Introduction Recently, with the rise of large language models and AI, we have seen innumerable advancements in natural language processing. Models in domains like text, code, and image/video generation have archived human-like reasoning and performance.

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