Unite.AI

NOVEMBER 8, 2023

Natural Language Processing (NLP) has experienced some of the most impactful breakthroughs in recent years, primarily due to the the transformer architecture. The introduction of word embeddings, most notably Word2Vec, was a pivotal moment in NLP. One-hot encoding is a prime example of this limitation.

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John Snow Labs

MAY 10, 2023

NLP is the technological innovator across every industry as it is shaping the future of humanity in various ways. With the support of NLP, doctors can be better equipped to make better diagnoses and analyze patients’ conditions. Significance of NLP in Healthcare Let’s discuss some uses of NLP in Healthcare.

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Lexalytics

MAY 25, 2021

One of the most important and most-used functions in text analytics and NLP is sentiment analysis — the process of determining whether a word, phrase, or document is positive, negative, or neutral. At Lexalytics, an InMoment company, our approach has been to hand-categorize content into polar and non-polar groups.

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John Snow Labs

SEPTEMBER 17, 2024

Clinical data abstraction refers to the process of finding and recording relevant administrative and clinical data pieces. This NLP clinical solution collects data for administrative coding tasks, quality improvement, patient registry functions, and clinical research.

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John Snow Labs

MAY 24, 2023

Therefore, the data needs to be properly labeled/categorized for a particular use case. In this article, we will discuss the top Text Annotation tools for Natural Language Processing along with their characteristic features. Top Text Annotation Tools for NLP Each annotation tool has a specific purpose and functionality.

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IBM Journey to AI blog

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

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NVIDIA Developer

JUNE 2, 2021

Applications for natural language processing (NLP) have exploded in the past decade. Modern techniques can capture the nuance, context, and sophistication of language, just as humans do. Multiple-choice questions evaluate students’ understanding of the NLP concepts presented in the class.

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Becoming Human

MAY 9, 2024

Artificial intelligence, machine learning, natural language processing, and other related technologies are paving the way for a smarter “everything.” Where interpreting raw financial data has become easier NLP, it is also helping us make better predictions and financial decisions. How Does Data Labeling Work in Finance?

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ODSC - Open Data Science

SEPTEMBER 12, 2024

Now that artificial intelligence has become more widely accepted, some daring companies are looking at natural language processing (NLP) technology as the solution. Naturally, its high penetration rate has given way to exploration into machine learning subsets like deep learning and NLP.

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Flipboard

FEBRUARY 16, 2023

Natural language processing ( NLP ), while hardly a new discipline, has catapulted into the public consciousness these past few months thanks in large part to the generative AI hype train that is ChatGPT. million ($2.9 million ($2.9

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John Snow Labs

AUGUST 21, 2023

We are delighted to announce a suite of remarkable enhancements and updates in our latest release of Healthcare NLP. It is a testament to our commitment to continuously innovate and improve, furnishing you with a more sophisticated and powerful toolkit for healthcare natural language processing.

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John Snow Labs

JUNE 26, 2024

This blog post explores how John Snow Labs’ Healthcare NLP models are revolutionizing the extraction of critical insights on opioid use disorder. Traditional data analysis methods often fall short due to the unstructured nature of most medical data, such as clinical notes, patient records, and research articles.

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Probably Approximately a Scientific Blog

JANUARY 12, 2021

In NLP, dialogue systems generate highly generic responses such as “I don’t know” even for simple questions. Figure 1: adversarial examples in computer vision (left) and natural language processing tasks (right). Is commonsense knowledge already captured by pre-trained language models?

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Heartbeat

AUGUST 23, 2023

But what if there was a technique to quickly and accurately solve this language puzzle? Enter Natural Language Processing (NLP) and its transformational power. This is the promise of NLP: to transform the way we approach legal discovery. But exactly what is NLP , and how can it facilitate legal discovery?

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Heartbeat

JUNE 22, 2023

Yet not all chatbots are made equal, and some are more adept than others in deciphering and answering natural language questions. Natural language processing (NLP) can help with this. What is NLP? Sentiment analysis, language translation, and speech recognition are a few NLP applications.

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Topbots

APRIL 11, 2023

In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. This model marked a new era in NLP with pre-training of language models becoming a new standard. What is the goal? accuracy on SQuAD 1.1

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John Snow Labs

APRIL 30, 2024

This article will delve into the significance of NER (Named Entity Recognition) detection in OCR (Optical Character Recognition) and showcase its application through the John Snow Labs NLP library with visual features installed. How does Visual NLP come into action? What are the components that will be used for NER in Visual NLP?

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Marktechpost

MAY 5, 2024

Consequently, there’s been a notable uptick in research within the natural language processing (NLP) community, specifically targeting interpretability in language models, yielding fresh insights into their internal operations. Recent approaches automate circuit discovery, enhancing interpretability.

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Unite.AI

AUGUST 11, 2024

Users can set up custom streams to monitor keywords, hashtags, and mentions in real-time, while the platform's AI-powered sentiment analysis automatically categorizes mentions as positive, negative, or neutral, providing a clear gauge of public perception.

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The MLOps Blog

MARCH 23, 2023

NLP models in commercial applications such as text generation systems have experienced great interest among the user. These models have achieved various groundbreaking results in many NLP tasks like question-answering, summarization, language translation, classification, paraphrasing, et cetera.

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Pickl AI

JULY 4, 2023

Natural Language Processing (NLP) makes use of Machine Learning algorithms for organising and understanding human language. NLP helps machines to not only gather text and speech but also in identifying the core meaning that it needs to respond to. Read the blog to know more about Tokenization in NLP.

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Marktechpost

MAY 9, 2024

In Natural Language Processing (NLP) tasks, data cleaning is an essential step before tokenization, particularly when working with text data that contains unusual word separations such as underscores, slashes, or other symbols in place of spaces. The post Is There a Library for Cleaning Data before Tokenization?

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Unite.AI

JUNE 2, 2023

Based on this, it makes an educated guess about the importance of incoming emails, and categorizes them into specific folders. In addition to the smart categorization of emails, SaneBox also comes with a feature named SaneBlackHole, designed to banish unwanted emails.

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John Snow Labs

MAY 19, 2023

Natural Language Processing ( NLP ) is changing the way the legal sector operates. According to a report, the NLP market size is expected to reach $27.6 NLP understands and predicts law, converts unstructured text into a meaningful format that computers can understand and analyze. billion by 2026.

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Marktechpost

FEBRUARY 22, 2024

In computer vision, convolutional networks acquire a semantic understanding of images through extensive labeling provided by experts, such as delineating object boundaries in datasets like COCO or categorizing images in ImageNet. This approach has demonstrated effectiveness in natural language processing and reinforcement learning.

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Marktechpost

APRIL 30, 2024

PEFT’s applicability extends beyond Natural Language Processing (NLP) to computer vision (CV), garnering interest in fine-tuning large-parameter vision models like Vision Transformers (ViT) and diffusion models, as well as interdisciplinary vision-language models.

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John Snow Labs

OCTOBER 19, 2023

Understanding the Impact of Bias on NLP Models Why test NLP models for Bias? Natural Language Processing (NLP) models rely heavily on bias to function effectively. This is due to the fact that bias helps NLP models to identify important features and relationships among data points.

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Heartbeat

JULY 11, 2023

Photo by Oleg Laptev on Unsplash By improving many areas of content generation, optimization, and analysis, natural language processing (NLP) plays a crucial role in content marketing. It entails employing algorithms and techniques to process and extract meaning from human language. articles, videos).

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Snorkel AI

JANUARY 11, 2023

To help brands maximize their reach, they need to constantly and accurately categorize billions of YouTube videos. Using Snorkel Flow, Pixability leveraged foundation models to build small, deployable classification models capable of categorizing videos across more than 600 different classes with 90% accuracy in just a few weeks.

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Marktechpost

SEPTEMBER 20, 2024

Large language models (LLMs) have made significant leaps in natural language processing, demonstrating remarkable generalization capabilities across diverse tasks. These methods can be categorized into three main groups: pre-generation tuning, in-generation control, and post-generation parsing.

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ODSC - Open Data Science

MAY 24, 2023

Generative NLP Models in Customer Service: Evaluating Them, Challenges, and Lessons Learned in Banking Editor’s note: The authors are speakers for ODSC Europe this June. Be sure to check out their talk, “ Generative NLP models in customer service. How to evaluate them?

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Marktechpost

JULY 1, 2024

Natural language processing (NLP) is a branch of artificial intelligence focusing on the interaction between computers and humans using natural language. Despite the advancements in NLP, language models are still vulnerable to malicious attacks that exploit their weaknesses. unique clusters.

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AWS Machine Learning Blog

JUNE 25, 2024

Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. Businesses can use LLMs to gain valuable insights, streamline processes, and deliver enhanced customer experiences. No explanation is required.

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IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g.,

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Marktechpost

MAY 7, 2024

The rapid advancement of Large Language Models (LLMs) has sparked interest among researchers in academia and industry alike. Moreover, differences in data table structures between BI and traditional SQL contexts further complicate the translation process.

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Marktechpost

DECEMBER 18, 2023

The attention mechanism has played a significant role in natural language processing and large language models. The researchers emphasized that transformers utilize an old-school method similar to support vector machines (SVM) to categorize data into relevant and non-relevant information. Check out the Paper.

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Marktechpost

APRIL 10, 2024

The abundance of web-scale textual data available has been a major factor in the development of generative language models, such as those pretrained as multi-purpose foundation models and tailored for particular Natural Language Processing (NLP) tasks.

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