Key Skills

Software

AWS SageMaker

Anno-Mage

Appen

LabelImg

Doccano

Label Studio

Top Subject Matter

Skill assessment

Emotion analysis

Multi-model

Top Data Types

3D Sensor

Audio

Computer Code Programming

Top Label Types

Action Recognition

Audio Recording

Bounding Box

Classification

Data Collection

Freelancer Overview

A motivated and detail-oriented IT student pursuing a Master of Information Technology (AI specialization) at The University of Western Australia. Skilled in data labeling, AI model training, and technical problem-solving, with experience in programming and machine learning. Seeking opportunities to contribute to AI data standardization and training projects.

Labeling Experience

Sentiment Analysis Assistant

DoccanoTextSegmentation

Collected and cleaned large-scale text data from Twitter using web scraping tools. Applied natural language processing (NLP) techniques to classify sentiment. Achieved sentiment prediction accuracy of 85% using Scikit-learn.

Collected and cleaned large-scale text data from Twitter using web scraping tools. Applied natural language processing (NLP) techniques to classify sentiment. Achieved sentiment prediction accuracy of 85% using Scikit-learn.

2024 - 2024

Chatbot Development labeler

DoccanoTextText SummarizationEvaluation Rating

Developed a rule-based chatbot using Python and Natural Language Toolkit (NLTK) Annotated text datasets for intent recognition and entity extraction Deployed chatbot to answer common queries, improving response efficiency by 40%

Developed a rule-based chatbot using Python and Natural Language Toolkit (NLTK) Annotated text datasets for intent recognition and entity extraction Deployed chatbot to answer common queries, improving response efficiency by 40%

2024 - 2024

AI-Powered Image Classification Labeler

LabelimgImageClassificationText Generation

Preprocessed and labeled image datasets for supervised learning using LabelImg and OpenCV. Trained models using TensorFlow, achieving a 90% accuracy on test data. Designed and implemented data augmentation techniques to improve model robustness.

Preprocessed and labeled image datasets for supervised learning using LabelImg and OpenCV. Trained models using TensorFlow, achieving a 90% accuracy on test data. Designed and implemented data augmentation techniques to improve model robustness.

2024 - 2024

Annotation Assistant

Label StudioVideoEmotion RecognitionTracking

Object Detection: Identifying and bounding objects such as faces, eyes, lips, brushes, makeup products, and specific areas of the face Semantic Segmentation: Pixel-level labeling to classify each pixel in the image into different categories like skin, makeup, background, or different makeup products Action Recognition: Labeling actions performed in the video, such as applying eyeshadow, blending foundation, or contouring Tracking: Following the movement of objects or people over time, such as tracking a brush as it's applied to the face

Object Detection: Identifying and bounding objects such as faces, eyes, lips, brushes, makeup products, and specific areas of the face Semantic Segmentation: Pixel-level labeling to classify each pixel in the image into different categories like skin, makeup, background, or different makeup products Action Recognition: Labeling actions performed in the video, such as applying eyeshadow, blending foundation, or contouring Tracking: Following the movement of objects or people over time, such as tracking a brush as it's applied to the face

2023 - 2023

Education

Work History