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Ting-an Lu

Ting-an Lu

LLM Specialist | Data-Driven Insights | AWS-Optimized NLP Solutions

Taiwan flagTaipei, Taiwan
$18.00/hrIntermediateOther

Key Skills

Software

Other

Top Subject Matter

LLM evalution in Mandarin/Chinese
Sentiment Analysis
Prediction Model

Top Data Types

TextText

Top Task Types

Classification
Data Collection
Entity Ner Classification
Fine Tuning

Freelancer Overview

I have extensive experience in data labeling and AI training, particularly in the domain of sentiment analysis and natural language processing (NLP) using large language models (LLMs). My work has involved curating and labeling data for complex political texts, leveraging advanced models like BERT and ChatGPT to capture nuanced sentiments. I have successfully executed projects that required precise sentiment classification, which I then used to train robust AI models, contributing to more accurate predictive analytics. My skills in utilizing cloud-based platforms such as AWS for NLP model deployment further enhance the efficiency and scalability of my solutions. My background in project management, combined with my technical expertise in SQL and machine learning tools, uniquely positions me to drive impactful data-driven AI projects.

IntermediateEnglishChinese Mandarin

Labeling Experience

Research Assistant

OtherTextEntity Ner ClassificationClassification
In my capstone project, I analyzed sentiments in U.S. political discourse related to the World Trade Organization (WTO) using advanced NLP techniques. I labeled and categorized 1,089 political messages with tools like ChatGPT-4 and BERT, focusing on the nuanced sentiments within these texts. The project involved implementing Entity-Based Sentiment Analysis and deploying models on AWS to efficiently process large datasets. The results provided insights into how WTO activities influence U.S. political sentiments, contributing to the broader discussion on national sovereignty.

In my capstone project, I analyzed sentiments in U.S. political discourse related to the World Trade Organization (WTO) using advanced NLP techniques. I labeled and categorized 1,089 political messages with tools like ChatGPT-4 and BERT, focusing on the nuanced sentiments within these texts. The project involved implementing Entity-Based Sentiment Analysis and deploying models on AWS to efficiently process large datasets. The results provided insights into how WTO activities influence U.S. political sentiments, contributing to the broader discussion on national sovereignty.

2023 - 2024

Education

U

University of California, San Diego

Master of Science in Computational Social Science, Computational Social Science

Master of Science in Computational Social Science
2023 - 2024

Work History

L

LINE Bank Taiwan

Associste Project Manager

Taipei
2023 - 2023