Unite.AI

OCTOBER 12, 2023

However, the more innovative paper in my view, is a paper with the second-most citations, a 2011 paper titled “ Memory-Based Approximation of the Gaussian Mixture Model Framework for Bandwidth Extension of Narrowband Speech “ In that work, I proposed a new statistical modeling technique that incorporates temporal information in speech.

Machine Learning 278

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NVIDIA

NOVEMBER 15, 2023

That’s when researchers in information retrieval prototyped what they called question-answering systems, apps that use natural language processing ( NLP ) to access text, initially in narrow topics such as baseball. IBM’s Watson became a TV celebrity in 2011 when it handily beat two human champions on the Jeopardy!

Generative AI 131

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Topbots

JUNE 22, 2023

SA is a very widespread Natural Language Processing (NLP). Hence, whether general domain ML models can be as capable as domain-specific models is still an open research question in NLP. Other articles in my line of research (NLP, RL) Lima Paiva, F. Journal of Finance (2011), 66(1):35–65. Bianchi, R.

Machine Learning 107

Machine Learning ChatGPT Natural Language Processing Categorization 107

Unite.AI

NOVEMBER 10, 2024

It uses natural language processing (NLP) algorithms to understand the context of conversations, meaning it's not just picking up random mentions! Brand24 was founded in 2011 and is based in Wrocław, Poland. They've managed to snag some pretty impressive clients like Intel, H&M, and IKEA!

Categorization 147

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AWS Machine Learning Blog

DECEMBER 14, 2023

Established in 2011, Talent.com aggregates paid job listings from their clients and public job listings, and has created a unified, easily searchable platform. The readers can refer to the tutorial for setting up and running SageMaker Processing jobs.

ETL 102

ETL Data Scientist Machine Learning Deep Learning 102

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). abs/2005.03993 Andrew L.

Neural Network 52

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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. 10 years on, little thus seems to have changed.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Probably Approximately a Scientific Blog

AUGUST 28, 2016

In ACL 2011. The rise of crowdsourcing. Wired magazine 14.6 Zaidan and Chris Callison-Burch Crowdsourcing translation: professional quality from non-professionals.

NLP 52

NLP Explainability Natural Language Processing 52

Lexalytics

APRIL 5, 2021

Fast-forward a couple of decades: I was (and still am) working at Lexalytics, a text-analytics company that has a comprehensive NLP stack developed over many years. This is the sort of representation that is useful for natural language processing. I was out of the neural net biz. and BERT.

Neural Network 52

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Explosion

FEBRUARY 12, 2017

The Quora dataset is an example of an important type of Natural Language Processing problem: text-pair classification. The question of how idealised NLP experiments should be is not new. The model is implemented using Thinc , a small library of NLP-optimized machine learning functions being developed for use in spaCy.

Neural Network 40

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Explosion

MARCH 17, 2019

of the spaCy Natural Language Processing library includes a huge number of features, improvements and bug fixes. Most NLP projects are easier if you have a way to train models on exactly your data. spaCy is an open-source library for industrial-strength natural language processing in Python.

NLP 52

NLP Python Neural Network Natural Language Processing 52

Sebastian Ruder

OCTOBER 26, 2019

Cross-lingual learning in the transfer learning taxonomy ( Ruder, 2019 ) Methods from domain adaptation have also been applied to cross-lingual transfer ( Prettenhofer & Stein, 2011 , Wan et al., Cross-lingual learning might be useful—but why should we care about applying NLP to other languages in the first place?

BERT 52

BERT NLP Neural Network Natural Language Processing 52

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.,

BERT 52

BERT NLP Natural Language Processing Computational Linguistics 52

Artificial Corner

JUNE 6, 2023

Natural Language Processing (NLP) techniques can be applied to analyze and understand unstructured text data. The integration of AI and ML into data engineering pipelines enables a wide range of applications. For example, predictive analytics models can be trained on historical data to make accurate forecasts.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

Explosion

DECEMBER 17, 2013

Natural languages introduce many unexpected ambiguities, which our world-knowledge immediately filters out. You should probably at least skim that post before reading this one, unless you’re very familiar with NLP research. Syntactic Processing Using the Generalized Perceptron and Beam Search.

Python 45

Python Algorithm NLP Computational Linguistics 45

AWS Machine Learning Blog

NOVEMBER 11, 2024

text generation model on domain-specific datasets, enabling it to generate relevant text and tackle various natural language processing (NLP) tasks within a particular domain using few-shot prompting. This fine-tuning process involves providing the model with a dataset specific to the target domain.

Generative AI 109

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AWS Machine Learning Blog

JULY 20, 2023

They have been proven to be efficient in diverse applications and learning settings such as cybersecurity [1] and fraud detection, remote sensing, predicting best next steps in financial decision-making, medical diagnosis, and even computer vision and natural language processing (NLP) tasks. References [1] Raj Kumar, P.

ML 89

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ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thanks for reading!

Neural Network 52

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Probably Approximately a Scientific Blog

NOVEMBER 12, 2016

In the my introductory post about NLP I introduced the following survey question: when you search something in Google (or any other search engine of your preference), is your query: (1) a full question, such as "What is the height of Mount Everest?" (2) On February 2011, Watson competed in Jeopardy against former winners of the show, and won!

NLP 52

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