Melek Gdhami

•Optimized a machine-learning model, resulting in a 97% prediction accuracy. •Implemented the model into a user-friendly web application using Streamlit, making the solution accessible to non-technical users. Technologies: Python, Jupyter, Machine Learning, Numpy, Flask, Pandas, Streamlit, scikit-learn.

•Processed time-series data to calculate relevant features for machine learning models. •Prepared data pipelines to build models for energy consumption prediction with a high level of accuracy of 95%. Technologies: Python, Jupyter, Machine Learning, Numpy, Pandas, scikit-learn.

• Automated resume scraping from LinkedIn and Google Images, increasing data collection efficiency by 50%. • Implemented OCR and image labeling techniques, achieving a 98% text conversion accuracy. Technologies: Deep Learning, Computer Vision, Web Scraping, Numpy, PyTorch, Pandas, scikit-learn, BeautifulSoup.

• Developed and cleaned datasets to build machine-learning models predicting job offers, with an accuracy of 97%. Technologies: Machine Learning, Numpy, Pandas, React Native, Google Colaboratory.