Nwaba P.

Key Skills

Software

Other

Labelbox

Top Subject Matter

Object detection annotation practice dataset

Text classification and NER annotation exercise

Multimodal ML dataset labeling (image, text, audio)

Top Data Types

Image

Text

Audio

Document

Top Task Types

Object Detection

Entity (NER) Classification

Transcription

Freelancer Overview

Image Annotation Practice Dataset (2025). Core strengths include Other and Labelbox. Education includes Bachelor of Science, Alex Ekwueme Federal University. AI-training focus includes data types such as Image, Text, and Audio and labeling workflows including Object Detection, Entity (NER) Classification, and Transcription.

Labeling Experience

Data Annotator (Image/Text/Audio labeling)

LabelboxAudioTranscription

Gained hands-on experience labeling audio data for machine learning projects, including transcription-oriented annotation workflows. Followed annotation guidelines carefully to maintain high accuracy. Used annotation platforms such as Labelbox, CVAT, and Label Studio to produce consistent dataset annotations. • Label audio inputs for transcription-related tasks • Apply guideline adherence to ensure label quality • Use labeling platforms to maintain consistent formatting • Perform QA checks to detect and correct errors

2025 - Present

Text Classification Exercise (2025)

OtherTextEntity (NER) Classification

Performed sentiment labeling and named entity recognition on 800+ text samples. Followed multi-step annotation guidelines with 100% compliance during peer review. Ensured consistent application of label definitions across examples. • Assigned sentiment labels to text segments • Identified and labeled named entities for NER • Followed multi-step guidelines for annotation consistency • Passed peer-review compliance checks with no guideline violations

2025 - 2025

Image Annotation Practice Dataset (2025)

OtherImageObject Detection

Annotated a set of 1,500+ images for object detection tasks using bounding boxes and polygons. Maintained 95%+ accuracy compared with provided gold standard labels. Documented edge cases and suggested guideline improvements to improve labeling consistency. • Created bounding box annotations for detected objects • Drew polygon regions for more precise object delineation • Verified annotations against gold standard labels to maintain accuracy • Logged edge cases and recommended guideline refinements

2025 - 2025

Education

Work History