Categorization, Data Quality and Natural Language Processing

Decoding the DNA of Large Language Models: A Comprehensive Survey on Datasets, Challenges, and Future Directions

Marktechpost

MARCH 10, 2024

Developing and refining Large Language Models (LLMs) has become a focal point of cutting-edge research in the rapidly evolving field of artificial intelligence, particularly in natural language processing. A significant innovation in this domain is creating a specialized tool to refine the dataset compilation process.

Large Language Models

Large Language Models Natural Language Processing LLM Categorization

5 Key Open-Source Datasets for Named Entity Recognition

Becoming Human

MAY 9, 2024

In this article, we’ll talk about what named entity recognition is and why it holds such an integral position in the world of natural language processing. Introduction about NER Named entity recognition (NER) is a fundamental aspect of natural language processing (NLP). Disadvantages 1.Data

Natural Language Processing

Natural Language Processing NLP Categorization Data Mining

NLP in Legal Discovery: Unleashing Language Processing for Faster Case Analysis

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. But what if there was a way to unravel this language puzzle swiftly and accurately? However, in this sea of complexity, NLP offers a ray of hope.

NLP

NLP Natural Language Processing Algorithm Categorization

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Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction

Towards AI

FEBRUARY 20, 2024

If you want an overview of the Machine Learning Process, it can be categorized into 3 wide buckets: Collection of Data: Collection of Relevant data is key for building a Machine learning model. It isn't easy to collect a good amount of quality data. How Machine Learning Works?

Machine Learning

Machine Learning ML Neural Network Algorithm

Building Domain-Specific Custom LLM Models: Harnessing the Power of Open Source Foundation Models

Towards AI

MAY 20, 2023

Challenges of building custom LLMs Building custom Large Language Models (LLMs) presents an array of challenges to organizations that can be broadly categorized under data, technical, ethical, and resource-related issues. Ensuring data quality during collection is also important.

LLM

LLM Large Language Models Chatbots Natural Language Processing

Unmasking the Biases Within AI: How Gender, Ethnicity, Religion, and Economics Shape NLP and Beyond

John Snow Labs

OCTOBER 19, 2023

Natural Language Processing (NLP) models rely heavily on bias to function effectively. In fact, a certain degree of bias is essential for these models to make accurate predictions and decisions based on patterns within the data they have been trained on. harness.generate().run().report()

NLP

NLP Natural Language Processing AI AI

A Guide to Convolutional Neural Networks

Heartbeat

AUGUST 21, 2023

AlexNet was created to categorize photos in the ImageNet dataset, which contains approximately 1 million images divided into 1,000 categories. Natural Language Processing : CNNs have been implemented for sentiment analysis and text categorization in natural language processing jobs.

Convolutional Neural Networks

Convolutional Neural Networks Neural Network Natural Language Processing Computer Vision

How AI saves money and improves banking complaint handling

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Assigning complaints to staff.

Large Language Models

Large Language Models AI AI Natural Language Processing

How AI saves money and improves banking complaint handling

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Assigning complaints to staff.

Large Language Models

Large Language Models AI AI Natural Language Processing

How AI saves money and improves banking complaint handling

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Assigning complaints to staff.

Large Language Models

Large Language Models AI AI Natural Language Processing

How we built better GenAI with programmatic data development

Snorkel AI

JULY 19, 2023

The RedPajama project aims to create a set of leading, fully open-source models (LLMs) for natural language processing, including not just open model weights, but also open training data. Background: what is RedPajama? For these experiments, we use the RedPajama family of LLMs.

Categorization

Categorization ChatGPT Large Language Models Generative AI

How we built better GenAI with programmatic data development

Snorkel AI

JULY 19, 2023

The RedPajama project aims to create a set of leading, fully open-source models (LLMs) for natural language processing, including not just open model weights, but also open training data. Background: what is RedPajama? For these experiments, we use the RedPajama family of LLMs.

Categorization

Categorization ChatGPT Large Language Models Generative AI

How we built a better GenAI with programmatic data development

Snorkel AI

JULY 19, 2023

The RedPajama project aims to create a set of leading, fully open-source models (LLMs) for natural language processing, including not just open model weights, but also open training data. Background: what is RedPajama? For these experiments, we use the RedPajama family of LLMs.

Categorization

Categorization ChatGPT Large Language Models Generative AI

Build a classification pipeline with Amazon Comprehend custom classification (Part I)

AWS Machine Learning Blog

SEPTEMBER 14, 2023

Amazon Comprehend is a natural-language processing (NLP) service that uses machine learning to uncover valuable insights and connections in text. Knowledge management – Categorizing documents in a systematic way helps to organize an organization’s knowledge base. This allows for better monitoring and auditing.

Categorization

Categorization Machine Learning Data Scientist Natural Language Processing

Deep Learning Challenges in Software Development

Heartbeat

AUGUST 29, 2023

Deep learning is a branch of machine learning that makes use of neural networks with numerous layers to discover intricate data patterns. Deep learning models use artificial neural networks to learn from data. Natural Language Processing (NLP) : Question answering, language modeling, sentiment analysis, machine translation, and more.

Software Development

Software Development Deep Learning Neural Network Convolutional Neural Networks

Training Improved Text Embeddings with Large Language Models

Unite.AI

JANUARY 11, 2024

They serve as a core building block in many natural language processing (NLP) applications today, including information retrieval, question answering, semantic search and more. With further research intoprompt engineering and synthetic data quality, this methodology could greatly advance multilingual text embeddings.

Large Language Models

Large Language Models Prompt Engineer Prompt Engineering BERT

How Pixability uses foundation models to accelerate NLP application development by months

Snorkel AI

JANUARY 11, 2023

Pixability is a data and technology company that allows advertisers to quickly pinpoint the right content and audience on YouTube. To help brands maximize their reach, they need to constantly and accurately categorize billions of YouTube videos. Using AI to help customers optimize ad spending and maximize their reach on YouTube.

NLP

NLP Auto-classification Categorization Natural Language Processing

Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights

AWS Machine Learning Blog

NOVEMBER 15, 2023

As a first step, they wanted to transcribe voice calls and analyze those interactions to determine primary call drivers, including issues, topics, sentiment, average handle time (AHT) breakdowns, and develop additional natural language processing (NLP)-based analytics.

Data Ingestion

Data Ingestion Metadata NLP Data Scientist

NeurIPS 2023: Key Takeaways From Invited Talks

Topbots

DECEMBER 19, 2023

The Many Faces of Responsible AI In her presentation , Lora Aroyo, a Research Scientist at Google Research, highlighted a key limitation in traditional machine learning approaches: their reliance on binary categorizations of data as positive or negative examples. In safety evaluation tasks, experts disagree on 40% of examples.

Computer Vision

Computer Vision Natural Language Processing AI Researcher AI Research

The Pros and Cons of Using the Top 5 Open-Source Named Entity Recognition Datasets

Defined.ai blog

APRIL 10, 2023

Named Entity Recognition (NER) is a natural language processing (NLP) subtask that involves automatically identifying and categorizing named entities mentioned in a text, such as people, organizations, locations, dates, and other proper nouns. What is Named Entity Recognition (NER)?

NLP

NLP Categorization Natural Language Processing Algorithm

The Pros and Cons of Using the Top 5 Open-Source Named Entity Recognition Datasets

Defined.ai blog

APRIL 10, 2023

Named Entity Recognition (NER) is a natural language processing (NLP) subtask that involves automatically identifying and categorizing named entities mentioned in a text, such as people, organizations, locations, dates, and other proper nouns. What is Named Entity Recognition (NER)?

NLP

NLP Categorization Natural Language Processing Algorithm

Extract non-PHI data from Amazon HealthLake, reduce complexity, and increase cost efficiency with Amazon Athena and Amazon SageMaker Canvas

AWS Machine Learning Blog

FEBRUARY 28, 2023

The high-level steps involved in the solution are as follows: Use AWS Step Functions to orchestrate the health data anonymization pipeline. Use Amazon Athena queries for the following: Extract non-sensitive structured data from Amazon HealthLake. Perform one-hot encoding with Amazon SageMaker Data Wrangler.

ML

ML Machine Learning Categorization NLP

IT Service Desk Chatbot: Automate your Service Desk

Chatbots Life

MAY 19, 2023

They achieve this by asking the user for input, seeking confirmation, and collecting essential data for back-end business systems, boosting data quality and avoiding mistakes. IT helpdesk chatbots with AI capabilities may use conversation history and other factors to detect the employee’s purpose and categorize them accordingly.

Chatbots

Chatbots Automation Auto-complete Natural Language Processing

Top Artificial Intelligence Companies To Work With In 2023

Dlabs.ai

DECEMBER 6, 2022

They’re the perfect fit for: Image, video, text, data & lidar annotation Audio transcription Sentiment analysis Content moderation Product categorization Image segmentation iMerit also specializes in extraction and enrichment for Computer Vision , NLP , data labeling, and other technologies.

Artificial Intelligence

Artificial Intelligence Artificial Intelligence Computer Vision Machine Learning

Artificial Intelligence Zone

Decoding the DNA of Large Language Models: A Comprehensive Survey on Datasets, Challenges, and Future Directions

5 Key Open-Source Datasets for Named Entity Recognition

Webinars

Trending Sources

NLP in Legal Discovery: Unleashing Language Processing for Faster Case Analysis

Webinars

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction

Building Domain-Specific Custom LLM Models: Harnessing the Power of Open Source Foundation Models

Unmasking the Biases Within AI: How Gender, Ethnicity, Religion, and Economics Shape NLP and Beyond

A Guide to Convolutional Neural Networks

How AI saves money and improves banking complaint handling

How AI saves money and improves banking complaint handling

How AI saves money and improves banking complaint handling

How we built better GenAI with programmatic data development

How we built better GenAI with programmatic data development

How we built a better GenAI with programmatic data development

Build a classification pipeline with Amazon Comprehend custom classification (Part I)

Deep Learning Challenges in Software Development

Training Improved Text Embeddings with Large Language Models

How Pixability uses foundation models to accelerate NLP application development by months

Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights

NeurIPS 2023: Key Takeaways From Invited Talks

The Pros and Cons of Using the Top 5 Open-Source Named Entity Recognition Datasets

The Pros and Cons of Using the Top 5 Open-Source Named Entity Recognition Datasets

Extract non-PHI data from Amazon HealthLake, reduce complexity, and increase cost efficiency with Amazon Athena and Amazon SageMaker Canvas

IT Service Desk Chatbot: Automate your Service Desk

Top Artificial Intelligence Companies To Work With In 2023

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