Elijah Onyango

Key Skills

Software

AWS SageMaker

Appen

Labelbox

SuperAnnotate

Other

Top Subject Matter

Natural Language Processing (NLP)

Media and Entertainment

satellite and image classification

Top Data Types

Audio

Computer Code Programming

Image

Top Task Types

Audio Recording

Bounding Box

Computer Programming Coding

Data Collection

Freelancer Overview

I have extensive experience in data labeling and AI training data, particularly in areas such as image annotation, text classification, and predictive modeling. My expertise includes using tools like Labelbox, Prodi.gy, and SuperAnnotate for various projects, such as annotating medical images, classifying texts for sentiment analysis, and preparing large datasets for machine learning applications. I have worked on diverse datasets, including sentiment analysis for customer feedback, and document categorization for legal and academic purposes. In addition to hands-on experience with labeling tools, I possess strong knowledge of machine learning workflows, ensuring that labeled data aligns with model requirements and optimizing datasets for better training outcomes. My proficiency in Python and machine learning frameworks enables me to automate parts of the labeling process and improve the efficiency of data annotation. I am committed to delivering high-quality labeled data that drives successful AI model training and improves predictive accuracy.

Labeling Experience

image recognition

SuperannotateImageBounding BoxData Collection

I worked on an image recognition project where I annotated images for object detection, focusing on identifying and classifying objects such as vehicles, pedestrians, and traffic signs in autonomous vehicle datasets. The project involved using tools like SuperAnnotate and RectLabel to label images, enabling the training of machine learning models for improved scene understanding and object recognition in autonomous driving systems.

I worked on an image recognition project where I annotated images for object detection, focusing on identifying and classifying objects such as vehicles, pedestrians, and traffic signs in autonomous vehicle datasets. The project involved using tools like SuperAnnotate and RectLabel to label images, enabling the training of machine learning models for improved scene understanding and object recognition in autonomous driving systems.

2022 - 2022

Education

Work History