Ahlem Aboud

Key Skills

Software

AWS SageMaker

Axiom AI

Data Annotation Tech

Label Studio

Top Subject Matter

Medical images

NLP

Data in online social media

Top Data Types

Computer Code Programming

Document

Image

Top Task Types

Classification

Computer Programming Coding

Emotion Recognition

Question Answering

Freelancer Overview

I have extensive experience in AI training data, particularly in data labeling, where I have worked on preparing, organizing, and annotating large datasets to ensure their accuracy and relevance for machine learning models. My background includes working with both structured and unstructured data across various domains, which has given me a deep understanding of the importance of high-quality labeled data in building reliable AI systems. I have collaborated with data science teams to develop guidelines for consistent labeling, ensuring that the data is well-prepared for supervised and unsupervised learning tasks. Additionally, I have hands-on experience with tools and platforms used for data annotation and have worked on projects involving image recognition, natural language processing, and predictive modeling. My focus has always been on maintaining high levels of accuracy and efficiency in data labeling to enhance the performance of AI models, and I am skilled at handling complex and large-scale datasets to meet project objectives.

Labeling Experience

AI for medical domain

Data Annotation TechImageSegmentationRelationship

In the medical domain, I have experience with image labeling for tasks such as diagnostic imaging, where accurate annotations are crucial for training AI models in detecting abnormalities, segmenting tissues, or identifying specific medical conditions. This process involves labeling medical images like X-rays, MRIs, or CT scans to help AI systems recognize patterns, such as tumors or fractures, by marking regions of interest (ROIs) and classifying findings.

In the medical domain, I have experience with image labeling for tasks such as diagnostic imaging, where accurate annotations are crucial for training AI models in detecting abnormalities, segmenting tissues, or identifying specific medical conditions. This process involves labeling medical images like X-rays, MRIs, or CT scans to help AI systems recognize patterns, such as tumors or fractures, by marking regions of interest (ROIs) and classifying findings.

2024

AI for online social media

Data Annotation TechTextClassificationText Summarization

In this project, the variability and complexity of social media language—such as slang, abbreviations, and emojis—require a careful and nuanced approach to ensure accurate labeling. I have significant experience in data labeling for text-based social media content, where I’ve worked on annotating posts, comments, and messages to train AI models for tasks such as sentiment analysis, content moderation, and topic categorization. This involves tagging data based on sentiment (positive, negative, neutral), identifying spam, or labeling topics and themes that align with specific objectives.

In this project, the variability and complexity of social media language—such as slang, abbreviations, and emojis—require a careful and nuanced approach to ensure accurate labeling. I have significant experience in data labeling for text-based social media content, where I’ve worked on annotating posts, comments, and messages to train AI models for tasks such as sentiment analysis, content moderation, and topic categorization. This involves tagging data based on sentiment (positive, negative, neutral), identifying spam, or labeling topics and themes that align with specific objectives.

2019 - 2020

Education

Work History