#nlp

#nlp

Privacy is a fundamental human right and is enforced through various international laws.

Overmasking in text sanitization may lead to unnecessary information loss, while many detected spans can remain in clear text with low re-identification risk.

Participating in ODSC East 2025 provides access to cutting-edge AI technologies and hands-on learning opportunities.

Data science's growth fueled by breakthroughs in machine learning requires foundational math skills for success.

Using a fine-tuned language model can improve privacy risk assessment in data anonymization through effective sequence labeling.

Combining diverse subfield methods is essential for handling heterogeneous, multilingual data in text mining and NLP projects.

Effective document parsing hinges on maintaining context and fidelity in unstructured data extraction.

To enhance chatbot performance, advanced techniques like Retrieval-Augmented Generation (RAG) leverage real-time external information sources for more accurate and contextually relevant responses.

Evaluating large language models (LLMs) is essential but poses significant challenges due to language diversity, model sensitivities, and data contamination.

The paper presents Direct Nash Optimization, enhancing large language model training by utilizing pair-wise preferences instead of traditional reward maximization.

Open-source NLP systems effectively identify social support and social isolation in psychiatric notes using rule-based and LLM approaches.

NLP systems struggled with emotional support categories due to data insufficiency.

Creating a gold standard data set for NLP requires diverse patient notes with targeted annotations to enhance accuracy in understanding social support and isolation.

Prompt engineering certifications enhance employability in the growing field of AI by bridging the skills gap for job seekers.

ChatGPT by OpenAI is a mature AI chatbot while Gemini by Google is still experimental. Both are powered by Large Language Models (LLMs) for human-like interactions.

OpenAI, with ChatGPT as its flagship product, was co-founded by Sam Altman, Elon Musk, and others, has shifted from a non-profit to a for-profit organization, now valued at $80 billion.

TextBlob simplifies sentiment analysis of user feedback, making it easier to identify exercise performance and areas needing improvement.

spaCy provides efficient and production-ready NLP tools for processing text with Python.

The project focuses on optimizing text content filtering for lot zoning in procurement processes.

Text mining and NLP have minimal application in procurement, highlighting a gap in research and practical methodologies.

The project aims to standardize data extraction from various file formats into a unified JSON format for easier machine accessibility.

Text mining and NLP techniques effectively identify lot references and item descriptions in procurement documents.

The project aims to dynamically create detailed supplier risk profiles by developing a structured database for contract and supplier information.

The article outlines a methodology for extracting structured data from tender documents, leveraging NLP techniques for procurement efficiency.

Large language models automate tasks and generate high-quality machine learning training datasets efficiently.

Large language models (LLMs) like OpenAI's ChatGPT can generate text based on prompts but are prone to factual inconsistencies and have been misused by students for fake research.

Prompt engineering is crucial for enhancing large language models by optimizing prompts to guide them in generating desired outputs.