Lachhab Meriem

Custom Resume Processing Pipeline - Implementation of an end-to-end pipeline for resume processing using PySpark, streamlining the recruitment workflow from resume loading to ATS-compliant formats. - Development of a custom transformer for converting resumes to images and detecting text regions with a YOLO model, tailored for complex multi-column layouts. - Utilization of advanced OCR technology to extract text, followed by generating structured JSON outputs via the Gemini API for ATS compatibility. - Creation of a web application integrating this pipeline, utilizing Flask for the backend and MongoDB for data management, with aggregation techniques to enhance profile search capabilities. The frontend was developed with React and Tailwind CSS for a responsive user interface. -Containerization of the entire project using Docker.

Skills: Machine Learning

Optimizing Ship Layover Management at the Port of Safi. Build a data-driven system to enhance the management of ship layovers at the Port of Safi. Through data analysis and predictive modeling, this initiative leverages historical data on ship arrivals, durations, and other relevant metrics to streamline operations, reduce waiting times, and optimize resource allocation Methodology : - Data Cleaning and Preprocessing - Feature Engineering - Model Selection and Training - Reporting and Metrics - Prediction and Visualization