Saleh Ismail

Key Skills

Software

Appen

Axiom AI

Clickworker

Toloka

Top Subject Matter

Text analysis for social media sentiment

Speech to text evaluation for customer service in Arabic

Natural Language Processing for Arabic text analysis

Top Data Types

Image

Text

Video

Top Task Types

Relationship

RLHF

Text Generation

Freelancer Overview

As a graduate of Arabic Language from the Faculty of Arts, I bring a unique skill set to AI data labeling and training, specializing in Arabic text analysis. With extensive experience in sentiment analysis, text classification, and natural language processing (NLP), I have worked on projects that involve evaluating and training AI models to process and understand Arabic text. I leverage my deep understanding of the language to ensure high accuracy in labeling datasets for various AI applications, including content moderation, semantic analysis, and automated translation systems. In addition to my expertise in Arabic language processing, I have contributed to AI training projects across multiple sectors, focusing on text annotation and speech-to-text systems. My experience includes working with both structured and unstructured data to create high-quality datasets that optimize the performance of machine learning models. I am skilled in using various data labeling tools and have collaborated on projects involving medical text annotation and social media sentiment analysis, consistently delivering results that support the development of robust AI systems.

Labeling Experience

Arabic Text Sentiment Analysis

AppenTextText GenerationText Summarization

I worked as a Lead Data Annotator on a project focused on Arabic text sentiment analysis for social media platforms. The project aimed to classify Arabic posts into positive, negative, and neutral sentiments while considering cultural and dialectical variations in the Arabic language.

I worked as a Lead Data Annotator on a project focused on Arabic text sentiment analysis for social media platforms. The project aimed to classify Arabic posts into positive, negative, and neutral sentiments while considering cultural and dialectical variations in the Arabic language.

2023 - 2023

Education

Work History