deepsense.ai

MAY 4, 2023

deepsense.ai’s research paper “TrelBERT: A pre-trained encoder for Polish Twitter” has been accepted for presentation at the 9th Biennial Workshop on Slavic NLP (SlavNLP-2023), a part of the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL).

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Marktechpost

AUGUST 15, 2024

Metaphor Components Identification (MCI) is an essential aspect of natural language processing (NLP) that involves identifying and interpreting metaphorical elements such as tenor, vehicle, and ground. The primary issue in MCI lies in the complexity and diversity of metaphors.

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NLP People

APRIL 10, 2019

Natural Language Processing has seen some major breakthroughs in the past years; with the rise of Artificial Intelligence, the attempt at teaching machines to master human language is becoming an increasingly popular field in academia and industry all over the world. University of St. Gallen The University of St.

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NYU Center for Data Science

JULY 24, 2024

Ravfogel is currently completing his PhD in the Natural Language Processing Lab at Bar-Ilan University, supervised by Prof. He brings a wealth of experience in natural language processing, representation learning, and the analysis and interpretability of neural models. Yoav Goldberg. By Stephen Thomas

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NLP People

MAY 18, 2018

Are you looking to study or work in the field of NLP? For this series, NLP People will be taking a closer look at the NLP education & development landscape in different parts of the world, including the best sites for job-seekers and where you can go for the leading NLP-related education programs on offer.

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Marek Rei

NOVEMBER 4, 2024

I have written short summaries of 68 different research papers published in the areas of Machine Learning and Natural Language Processing. Computational Linguistics 2022. link] Developing a system for the detection of cognitive impairment based on linguistic features. Nature Communications 2024.

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NLP People

JUNE 5, 2018

Are you looking to study or work in the field of NLP? For this series, NLP People will be taking a closer look at the NLP education & development landscape in different parts of the world, including the best sites for job-seekers and where you can go for the leading NLP-related education programs on offer.

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ODSC - Open Data Science

APRIL 3, 2023

Question Answering is the task in Natural Language Processing that involves answering questions posed in natural language. QA is a critical area of research in NLP, with numerous applications such as virtual assistants, chatbots, customer support, and educational platforms. Euro) in 2021. Iryna Gurevych.

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Mlearning.ai

FEBRUARY 19, 2023

You don’t need to have a PhD to understand the billion parameter language model GPT is a general-purpose natural language processing model that revolutionized the landscape of AI. GPT-3 is a autoregressive language model created by OpenAI, released in 2020 . What is GPT-3?

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Topbots

JUNE 15, 2023

Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. 70% of research papers published in a computational linguistics conference only evaluated English.[ Association for Computational Linguistics.

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Marktechpost

JULY 15, 2023

This year, a paper presented at the Association for Computational Linguistics (ACL) meeting delves into the importance of model scale for in-context learning and examines the interpretability of LLM architectures. These models, which are trained on extensive amounts of data, can learn in context, even with minimal examples.

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Viso.ai

JULY 18, 2024

LLMs are pre-trained on extensive data on the web which shows results after comprehending complexity, pattern, and relation in the language. LLMs apply powerful Natural Language Processing (NLP), machine translation, and Visual Question Answering (VQA).

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Sebastian Ruder

AUGUST 18, 2019

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP. In the span of little more than a year, transfer learning in the form of pretrained language models has become ubiquitous in NLP and has contributed to the state of the art on a wide range of tasks.

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Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). If CNNs are pre-trained the same way as transformer models, they achieve competitive performance on many NLP tasks [28]. Credit for the title image: Liu et al. Why is it important?   What happened?  

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Google Research AI blog

JULY 10, 2023

Posted by Malaya Jules, Program Manager, Google This week, the 61st annual meeting of the Association for Computational Linguistics (ACL), a premier conference covering a broad spectrum of research areas that are concerned with computational approaches to natural language, is taking place online.

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Heartbeat

FEBRUARY 21, 2023

Picture by Anna Nekrashevich , Pexels.com Introduction Sentiment analysis is a natural language processing technique which identifies and extracts subjective information from source materials using computational linguistics and text analysis. Spark NLP is a natural language processing library built on Apache Spark.

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Bugra Akyildiz

JULY 16, 2023

Google created a new learning path guides you through a curated collection of content on generative AI products and technologies, from the fundamentals of Large Language Models to how to create and deploy generative AI solutions on Google Cloud.

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Ines Montani

MAY 9, 2017

In this post I’ll share some lessons we’ve learned from running spaCy , the popular and fast-growing library for Natural Language Processing in Python. Challenges for open-source NLP One of the biggest challenges for Natural Language Processing is dealing with fast-moving and unpredictable technologies.

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AssemblyAI

SEPTEMBER 18, 2023

However, among all the modern-day AI innovations, one breakthrough has the potential to make the most impact: large language models (LLMs). These feats of computational linguistics have redefined our understanding of machine-human interactions and paved the way for brand-new digital solutions and communications.

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Sebastian Ruder

NOVEMBER 14, 2022

Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. At the same time, a wave of NLP startups has started to put this technology to practical use. Data is based on: ml_nlp_paper_data by Marek Rei.

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NLP People

JANUARY 2, 2019

Hundreds of researchers, students, recruiters, and business professionals came to Brussels this November to learn about recent advances, and share their own findings, in computational linguistics and Natural Language Processing (NLP). BERT is a new milestone in NLP.

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Topbots

JANUARY 30, 2023

Making the transition from classical language generation to recognising and responding to specific communicative intents is an important step to achieve better acceptance of user-facing NLP systems, especially in Conversational AI. Association for Computational Linguistics. [2] Association for Computational Linguistics.

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The MLOps Blog

JANUARY 25, 2023

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing. as these words do not make any sense to machines.

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Sebastian Ruder

FEBRUARY 23, 2023

For modular fine-tuning for NLP, check out our EMNLP 2022 tutorial. Fixed routing can select different modules for different aspects of the target setting such as task and language in NLP or robot and task in RL, which enables generalisation to unseen scenarios. We cover such methods for NLP in our EMNLP 2022 tutorial.

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John Snow Labs

DECEMBER 26, 2023

Sentiment analysis, a branch of natural language processing (NLP), has evolved as an effective method for determining the underlying attitudes, emotions, and views represented in textual information. The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011). Daly, Peter T.

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Sebastian Ruder

JUNE 6, 2022

Seeing the emergence of such multilingual multimodal approaches is particularly encouraging as it is an improvement over the previous year’s ACL where multimodal approaches mainly dealt with English (based on an analysis of “multi-dimensional” NLP research we did for an ACL 2022 Findings paper ). Hershcovich et al.

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Explosion

DECEMBER 28, 2019

Jan 15: The year started out with us as guests on the NLP Highlights podcast , hosted by Matt Gardner and Waleed Ammar of Allen AI. In the interview, Matt and Ines talked about Prodigy , where training corpora come from and the challenges of annotating data for an NLP system – with some ideas about how to make it easier. ?

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Analytics Vidhya

SEPTEMBER 22, 2019

Overview How do search engines like Google understand our queries and provide relevant results? Learn about the concept of information extraction We will apply. The post How Search Engines like Google Retrieve Results: Introduction to Information Extraction using Python and spaCy appeared first on Analytics Vidhya.

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AWS Machine Learning Blog

MAY 22, 2023

Amazon EBS is well suited to both database-style applications that rely on random reads and writes, and to throughput-intensive applications that perform long, continuous reads and writes. """, """ Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents.

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Applied Data Science

DECEMBER 23, 2022

In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. As humans we do not know exactly how we learn language: it just happens.

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AWS Machine Learning Blog

MARCH 2, 2023

Sentiment analysis and other natural language programming (NLP) tasks often start out with pre-trained NLP models and implement fine-tuning of the hyperparameters to adjust the model to changes in the environment. She has a technical background in AI and Natural Language Processing.

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NLP People

SEPTEMBER 12, 2017

This job brought me in close contact with a large number of IT researchers, and some of them happened to work in computational linguistics and machine learning. This was when I realized I might try to pursue this path too, as it would allow me to combine my passion for languages and interest in technologies.

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Snorkel AI

JUNE 14, 2023

Timo Mertens is the Head of ML and NLP Products at Grammarly. Let’s double-click into correctness to describe our approach on how technology, and specifically machine learning and natural language processing, can come together in a very user-centric way to solve real problems that our users face every single day.

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Machine Learning Natural Language Processing Data Scientist Computational Linguistics 52

Snorkel AI

JUNE 14, 2023

Timo Mertens is the Head of ML and NLP Products at Grammarly. Let’s double-click into correctness to describe our approach on how technology, and specifically machine learning and natural language processing, can come together in a very user-centric way to solve real problems that our users face every single day.

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Machine Learning Natural Language Processing Data Scientist Computational Linguistics 52

Ines Montani

FEBRUARY 8, 2017

I eventually started university at the age of 17, doing a degree of media science and language studies, a hybrid of linguistics, computational linguistics and phonetics. I started working with Matt , who had just released spaCy , an open-source library for Natural Language Processing.

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Sebastian Ruder

DECEMBER 6, 2021

For instance, questions that can be solved by string matching are easy in English but much harder in morphologically rich languages ( Clark et al., Among current key applications of NLP, QA has the lowest linguistic global utility, i.e. performance averaged across the world's languages ( Blasi et al.,

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Explosion

MAY 8, 2016

This means that an English-only NLP system can get away with some very useful simplifying assumptions. German is the perfect language to unwind these. German is also famous for its capacity to form really long words , another process that is driven by the morphological system. It’s a simplifying assumption. join('{word}/{tag}'.format(word=t.orth_,

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