Abraham Kalume

Key Skills

Software

Appen

Clickworker

CloudFactory

CVAT

Dataloop

Hasty

iMerit

Labelbox

Mindrift

OneForma

Remotasks

V7 Labs

Scale AI

Top Subject Matter

Technology

Education

Healthcare

Top Data Types

Image

Text

Video

Top Label Types

Bounding Box

Prompt Response Writing SFT

Segmentation

Text Generation

Text Summarization

Freelancer Overview

I also have experience with data labeling and AI training projects where organizing and tagging were the bases to bring machine learning models to perfection. Among my strong points, I have attention to detail, good analysis skills, and a fair understanding of various AI technologies. This also means that I have worked on various projects concerning image, text, and audio labeling, done at heightened levels of accuracy to ensure the proper training of AI systems. My ability to efficiently execute tasks and meet tight deadlines sets me apart in this area.

Labeling Experience

Data labeling/ Annotation

DataloopImageBounding Box

As a Data Labeler at CloudFactory with the tool DataLoop, the post was influential in the annotation of data for quality datasets of machine learning projects. Core activities to be performed include the following: 1. Image Annotation: Tag objects, regions, and attributes in images to high detail for training data. This was done through bounding boxes, segmentation tools, and specific criteria for labeling to enhance model accuracy. 2. Audio Annotation: Transcribed, labeled, and categorized audio clips; quite a significant portion of work was done to ascertain the identity of the speakers, detecting their emotions, and other relevant features. This will go a long way in helping realize robust speech recognition and audio analysis models. 3. Text Annotation: Performed named entity recognition, sentiment analysis, and intent classification on textual data. Key phrases and contextual elements were identified to make sure that complete training sets were available for natural language p

As a Data Labeler at CloudFactory with the tool DataLoop, the post was influential in the annotation of data for quality datasets of machine learning projects. Core activities to be performed include the following: 1. Image Annotation: Tag objects, regions, and attributes in images to high detail for training data. This was done through bounding boxes, segmentation tools, and specific criteria for labeling to enhance model accuracy. 2. Audio Annotation: Transcribed, labeled, and categorized audio clips; quite a significant portion of work was done to ascertain the identity of the speakers, detecting their emotions, and other relevant features. This will go a long way in helping realize robust speech recognition and audio analysis models. 3. Text Annotation: Performed named entity recognition, sentiment analysis, and intent classification on textual data. Key phrases and contextual elements were identified to make sure that complete training sets were available for natural language p

2021 - 2022

Data Labeling/annotation

Scale AIVideoBounding BoxPolygon

Data labeling was one of the prime areas I was into and accomplished in Remotasks. It entailed the annotation and categorization of various types of data images, videos, and text for enriching machine learning models. Review and tag data according to instructions to make data accurate and consistent. Key Responsibilities: 1. Annotation: Apply the tool to mark an image, draw bounding boxes, or label an object by using all the data in the dataset. 2. Quality Assurance: Ensure that labeling will be appropriately done to meet the required quality by often looking back at previously completed tasks to provide proper feedback. 3. Guideline Understanding: Familiarize yourself with specific project requirements and guidelines you will have so you may look into labeling data correctly, since it may call for special requirements towards the project. 4. Time Management: Adherence to time constraints with efficient workflow for maximum productivity at high-quality outputs. 5. Team Collaboration:

Data labeling was one of the prime areas I was into and accomplished in Remotasks. It entailed the annotation and categorization of various types of data images, videos, and text for enriching machine learning models. Review and tag data according to instructions to make data accurate and consistent. Key Responsibilities: 1. Annotation: Apply the tool to mark an image, draw bounding boxes, or label an object by using all the data in the dataset. 2. Quality Assurance: Ensure that labeling will be appropriately done to meet the required quality by often looking back at previously completed tasks to provide proper feedback. 3. Guideline Understanding: Familiarize yourself with specific project requirements and guidelines you will have so you may look into labeling data correctly, since it may call for special requirements towards the project. 4. Time Management: Adherence to time constraints with efficient workflow for maximum productivity at high-quality outputs. 5. Team Collaboration:

2019 - 2021

Education

Work History