• Led projects using advanced tools like Hugging Face and big language models to improve language technology.• Good at using TF-IDF, NER, and word2vec to enhance language applications for improved user interaction.• Strong in using Python, learning from data (machine learning), and analysing lots of data.• Developed a chatbot utilizing the RAG (Retriever-Augmented Generation) model to enhance user engagement and response accuracy.

Implementation of a participatory authentication service that will allow companies to protect their brands and their customers from counterfeiting.- System based on NFC technology.- Supervision of 3 employees.- Collect data for marketing services.

Implementation of a Machine Learning system for a resume parser using 4 models :- Yolo object detection to recognize the blocks- Face Recognition to extract photo ID- NLP model to label each blocks- NER model to extract every labelsTools : Python, NLP, Computer Vision, YOLO, Word2Vec.

Research the importance of creatives and it’s impact on advertising.- Use SPARK to work on big amount of data.- Data analysis on how optimize creatives for difference audiences.- Predictive model to estimate the performance of creatives visual and textual elements.

Image Analysis based on Deep Learning/Python, Opencv, YOLO Object Detector.- Worked on the YOLO object detector to detect the appearance of a brand on social networks.- Usage of Flask to create bounding box for the object detector.- Self learning using darkflow Github and tutorials on Coursera.

Developed a credit risk model using Python.- Dispatch work to create a credit risk model- Run analysis on a big amount of data, using R studio