Tassere Dianda

Key Skills

Software

Clickworker

CrowdSource

Remotasks

Scale AI

Top Subject Matter

self-driving cars image

LLM evaluation in French

Satellite Image classification

Top Data Types

3D Sensor

Computer Code Programming

Document

Top Task Types

Bounding Box

Computer Programming Coding

Cuboid

Freelancer Overview

With six to seven months of experience in data annotation on the Remostaks platform, I’ve developed a strong foundation in labeling and preparing high-quality datasets for AI and machine learning projects. My background in Computer Science, combined with a solid understanding of programming languages and mathematics, has enabled me to work efficiently with complex data labeling requirements, ensuring precise and consistent results. This experience has honed my attention to detail and ability to accurately interpret nuanced labeling guidelines. Key skills that set me apart include my technical proficiency in handling diverse data formats, understanding model requirements, and consistently meeting quality standards. My analytical abilities allow me to approach labeling tasks with a problem-solving mindset, ensuring that the data I produce is ready for seamless integration into machine-learning workflows. This role has also helped me build strong time management skills and adapt quickly to new projects or annotation tools.

Labeling Experience

Data Annotator

Scale AI3D SensorBounding BoxCuboid

In my current project, I’m working on a 3D data labeling task that involves creating precise cuboids around vehicles, unclassified moving objects, and pedestrians in data gathered through 3D sensors. The objective is to accurately label these entities in a way that enables AI models to detect, classify, and track objects within a 3D space. This type of annotation is essential for applications like autonomous driving, where understanding the spatial positioning and movement of objects is critical. The project is substantial in scope, dealing with large datasets that require meticulous attention to detail to ensure accuracy and consistency across annotations. Each labeled cuboid must adhere to strict quality standards regarding size, alignment, and classification, as these directly impact the performance of the AI models that use this data. Additionally, I am involved in prompt writing, which involves crafting scenario-based text prompts that simulate various real-world interactions for

In my current project, I’m working on a 3D data labeling task that involves creating precise cuboids around vehicles, unclassified moving objects, and pedestrians in data gathered through 3D sensors. The objective is to accurately label these entities in a way that enables AI models to detect, classify, and track objects within a 3D space. This type of annotation is essential for applications like autonomous driving, where understanding the spatial positioning and movement of objects is critical. The project is substantial in scope, dealing with large datasets that require meticulous attention to detail to ensure accuracy and consistency across annotations. Each labeled cuboid must adhere to strict quality standards regarding size, alignment, and classification, as these directly impact the performance of the AI models that use this data. Additionally, I am involved in prompt writing, which involves crafting scenario-based text prompts that simulate various real-world interactions for

2024

Education

Work History