Collins Okindo

Key Skills

Software

CVAT

Labelbox

Scale AI

Toloka

Other

Sama

Top Subject Matter

Self driving Cars object Detection

Image Recognition

scene classification

Top Data Types

Image

Video

Top Task Types

Bounding Box

Classification

Object Detection

Polygon

Segmentation

Freelancer Overview

I am responsible for accurately labeling various types of data such as images and video according to specific guidelines to train machine learning models. This involves using annotation tools to mark relevant information and ensuring high-quality and consistent annotations through quality control processes. I adhere to guidelines while providing feedback for improvement and collaborate closely with data scientists and machine learning engineers to understand project requirements and resolve ambiguities. Additionally, I maintain detailed documentation and stay updated through ongoing training to enhance the annotation process and contribute to the overall accuracy and efficiency of the machine learning models

Labeling Experience

Data Associate

SamaVideoBounding BoxPolygon

y primary task was to label data, which included tasks like categorizing text, drawing bounding boxes around objects in images and video. The project was sizable, involving thousands of data points that required consistent, high-quality annotation. To ensure accuracy, I followed strict guidelines and annotation protocols, performed regular quality checks, and participated in peer reviews to maintain uniformity across the dataset. The project adhered to predefined quality measures, such as accuracy thresholds (e.g., 95% or higher), consistency in labeling, and periodic audits to ensure compliance with project standards.

y primary task was to label data, which included tasks like categorizing text, drawing bounding boxes around objects in images and video. The project was sizable, involving thousands of data points that required consistent, high-quality annotation. To ensure accuracy, I followed strict guidelines and annotation protocols, performed regular quality checks, and participated in peer reviews to maintain uniformity across the dataset. The project adhered to predefined quality measures, such as accuracy thresholds (e.g., 95% or higher), consistency in labeling, and periodic audits to ensure compliance with project standards.

2023 - 2024

Education

Work History