D

deep learning

A Contextual-Enhanced LightGCN for Movie Recommendation Systems

A modular Clinical NLP Pipeline built to process and analyze unstructured medical text using both traditional machine learning and transformer-based approaches.

The project combines multiple components including OCR, text preprocessing, feature engineering, classification, named entity recognition, and visualization into a single end-to-end pipeline. It supports extracting clinical insights from raw documents and predicting medical categories using both TF-IDF + SVM and BERT-based models.

The system was designed and implemented as a structured Python project, with each stage separated into independent modules for scalability and maintainability.

Key Highlights

Built an end-to-end NLP pipeline for clinical text processing. Implemented SVM (≈51% accuracy) and BERT (≈77% accuracy) models. Integrated OCR for extracting text from medical documents. Performed Named Entity Recognition (NER) on clinical data. Designed modular architecture (src/) for clean code organization. Exported outputs for visualization and dashboard integration.

The VirtuaLearn3D++ open-source scientific software for 3D point clouds.

Fresh Class🍎, A deep learning web application that classifies 6 types of fruits into 'Good' or 'Bad' quality using MobileNetV2 CNN. Features a Next.js frontend with real-time image classification. Team members: -Salah Eddine Berredjem -Ziad Abadlia -Tesnim Lala Bouali -Ines Goutel -Imen Kanoua -Mohamed Saber Tata

This repo will have all resources, labs, data which I use/d on Kaggle Network

Predicting pathogenic potentials of short DNA reads with reverse-complement deep neural networks.

Old functions to play with neural networks. Developed in December 2024

PDE-based Group Equivariant CNNs for PyTorch

The Konstellation Runtime Engine (KRE) is an open-source software application designed to run, maintain and evolve any kind of Machine Learning and Deep Learning solution in production.

Sistema de inteligencia artificial basado en visión por computadora para la detección y segmentación de latas y botellas

This project is a re-implementation of FeatureNet using Tensorflow 2. With working segmentation code.

FakET: Simulating Cryo-Electron Tomograms with Neural Style Transfer

This is an implementation of a very simple neural network from scratch.

This project provides a deep learning approach to learn machining features from CAD models using a hierarchical graph convolutional neural network.

Protocol for network and expression integration to identify potential defense gene in host-pathogen interactions

Projet personnel de classification des maladies des feuilles d'arbre. Article technique disponible sur mon blog : https://boulayc.gitlab.io/blog/