Tuấn Anh Lê

Key Skills

Software

Data Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

Document

Geospatial Tiled Imagery

Image

Top Task Types

Action Recognition

Audio Recording

Bounding Box

Classification

Data Collection

Freelancer Overview

As a detail-oriented and linguistically skilled professional, I have developed a strong background in data labeling and AI training data, particularly in the realm of text-based projects. Particularli, I am working on AI agent and ML languages, my expertise lies in ensuring high-quality annotations that enhance the accuracy and efficiency of machine learning models. With a keen eye for detail and a deep understanding of linguistic nuances, I excel at tasks such as text classification, sentiment analysis, and language translation. My experience has equipped me with the ability to work efficiently in fast-paced environments while maintaining precision and consistency. One of my key strengths is my proficiency in Vietnamese, which allows me to contribute to projects requiring cultural and linguistic expertise. I am well-versed in evaluating and refining language models to ensure they meet the highest standards of accuracy and relevance. My passion for AI and data-driven solutions drives me to continuously update my skills and stay informed about the latest developments in the field. I am excited to leverage my expertise to support innovative AI projects and contribute to the development of more sophisticated language models.

Labeling Experience

Data annotation

Data Annotation TechTextEntity Ner Classification

This project involves performing Entity (NER) classification on 10,000 e-commerce product descriptions using Data Annotation Tech. The goal is to identify and categorize key entities such as product names, brands, materials, and features. We adhere to a rigorous quality assurance process, including double-blind annotation and regular audits, to ensure a minimum accuracy of 95%.

This project involves performing Entity (NER) classification on 10,000 e-commerce product descriptions using Data Annotation Tech. The goal is to identify and categorize key entities such as product names, brands, materials, and features. We adhere to a rigorous quality assurance process, including double-blind annotation and regular audits, to ensure a minimum accuracy of 95%.

2024 - 2024

Education

Work History