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Mohamed Abobakr

Mohamed Abobakr

Software Engineer with a strong foundation in AI, cloud integration

Egypt flagCairo, Egypt
$7.00/hrEntry LevelCVATLabelimgRoboflow

Key Skills

Software

CVATCVAT
LabelImgLabelImg
RoboflowRoboflow
Other

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code ProgrammingComputer Code Programming
ImageImage
TextText

Top Task Types

Classification
Prompt Response Writing SFT
Text Generation

Freelancer Overview

I am a Software Engineer with a strong background in AI, machine learning, and data preprocessing, with hands-on experience in building and training models across computer vision, natural language processing, and structured data. Through projects such as IMAGITALE, I worked on transforming text inputs into high-quality images using GPT and Stable Diffusion, requiring careful data structuring and consistency across datasets. Additionally, I have developed ML pipelines for loan prediction, banknote authentication, and image classification, which involved extensive data cleaning, feature engineering, and model evaluation. My expertise includes image classification, object detection, and text data preparation, as well as practical knowledge of frameworks like TensorFlow, scikit-learn, and OpenCV. With certifications in IBM Generative AI Foundations, AWS Generative AI Essentials, and IBM Enterprise Design Thinking, I bring both technical depth and an industry-recognized foundation in AI workflows. I am passionate about ensuring high-quality labeled datasets that improve model performance and deliver real-world value.

Entry LevelArabicEnglish

Labeling Experience

Pretrained Models for Image Classification

OtherImageSegmentationClassification
Implemented multiple deep learning architectures — LeNet-5, ResNet-50, Inception, and Xception — for image classification tasks on MNIST and CIFAR-10 datasets. Applied transfer learning and hyperparameter optimization to improve accuracy and generalization. Performed comprehensive model evaluation using precision, recall, F1-score, and confusion matrices, ensuring robust benchmarking across architectures.

Implemented multiple deep learning architectures — LeNet-5, ResNet-50, Inception, and Xception — for image classification tasks on MNIST and CIFAR-10 datasets. Applied transfer learning and hyperparameter optimization to improve accuracy and generalization. Performed comprehensive model evaluation using precision, recall, F1-score, and confusion matrices, ensuring robust benchmarking across architectures.

2024 - 2024

Wikipedia Text Summarization & Entity Extraction

OtherTextClassificationText Generation
Developed an NLP pipeline to process Wikipedia articles for automatic summarization and entity extraction. Implemented both extractive (TF-IDF, TextRank) and abstractive (transformer-based) summarization methods. Applied Named Entity Recognition (NER) with spaCy to extract structured entities (people, places, organizations) from unstructured text. Evaluated summarization quality using ROUGE and BLEU scores, creating a high-quality labeled dataset suitable for training and fine-tuning large language models.

Developed an NLP pipeline to process Wikipedia articles for automatic summarization and entity extraction. Implemented both extractive (TF-IDF, TextRank) and abstractive (transformer-based) summarization methods. Applied Named Entity Recognition (NER) with spaCy to extract structured entities (people, places, organizations) from unstructured text. Evaluated summarization quality using ROUGE and BLEU scores, creating a high-quality labeled dataset suitable for training and fine-tuning large language models.

2024 - 2024

Loan Prediction using Machine Learning

OtherTextClassificationEvaluation Rating
Built a Loan Prediction system to determine loan eligibility based on applicant information such as income, credit history, and loan amount. The project included data cleaning, feature engineering, and categorical encoding, followed by model training with Logistic Regression, Decision Trees, and Random Forests. Evaluated model performance with accuracy, precision, recall, and F1-score to ensure reliable predictions. Demonstrated skills in handling tabular datasets, preparing labeled data, and building models for real-world financial decision-making.

Built a Loan Prediction system to determine loan eligibility based on applicant information such as income, credit history, and loan amount. The project included data cleaning, feature engineering, and categorical encoding, followed by model training with Logistic Regression, Decision Trees, and Random Forests. Evaluated model performance with accuracy, precision, recall, and F1-score to ensure reliable predictions. Demonstrated skills in handling tabular datasets, preparing labeled data, and building models for real-world financial decision-making.

2023 - 2024

• IMAGITALE

OtherTextClassificationFine Tuning
IMAGITALE is an AI-powered storytelling platform that transforms user-written narratives into Disney-style stories and images. It integrates OpenAI GPT-3.5 for story generation and Stable Diffusion XL with DreamBooth & LoRA for image synthesis, requiring structured data alignment between text and images. Labeled datasets and evaluation tasks ensured consistency between narrative elements and generated visuals, improving both story coherence and image quality.

IMAGITALE is an AI-powered storytelling platform that transforms user-written narratives into Disney-style stories and images. It integrates OpenAI GPT-3.5 for story generation and Stable Diffusion XL with DreamBooth & LoRA for image synthesis, requiring structured data alignment between text and images. Labeled datasets and evaluation tasks ensured consistency between narrative elements and generated visuals, improving both story coherence and image quality.

2023 - 2024

Education

C

Cairo University

Bachelor of Science, Computer Science

Bachelor of Science
2020 - 2024

Work History

I

IBM

Cloud Integration Developer

Cairo
2024 - Present
D

Dstny (Tactful AI)

Software Development Intern

Cairo
2023 - 2023