LLM with graph augmentation for recommandations

Research project (in a team of 4 students) :

10/2024 - 05/2025

Abstract : Enhanced movie recommendations using LLMs (Gemini-1.5, Mistral) to enrich user/item profiles, significantly improving accuracy in LightGCN, MLP, and Matrix Factorization by addressing data sparsity and enabling nuanced personalization. Focused on responsible integration, acknowledging challenges like bias and cost.

Main tasks :

• Getting started with the dataset & understand the problematic of the need;
• Study and build a baseline with appropriate models for recommander systems (here: LightGCN, MLP and Matrix Factorization);
• Do prompt engineering and enrich the dataset by generating significant attributes;
• Perform MLOps on the new dataset(objective: Predict the rating);
• Study the impacts and leave recommendations regarding the approach.

Improving Part-of-Speech Tagging in English with TreeTagger

Research project (in a team of 4 students) :

01/2025 - 02/2025

Abstract: This paper explores the use of TreeTagger to accurately identify the different functions of the word "that" in English, such as conjunction, relative pronoun, determiner, or adverb. We first evaluate pre-trained models from the BNC and Penn corpora on a test dataset, then re-train TreeTagger with specific labels derived from the Brown corpus to enhance accuracy. Comparisons with other tools like Stanza and UDpipe are also presented. The main findings demonstrate that re-training with the Brown corpus significantly improves the tool’s performance and ability to distinguish among the various uses of "that".

Main Tasks:

• Data collection and preparation, including annotating the Brown corpus with specific labels.
• Initial evaluation of BNC and Penn models for categorizing "that".
• Re-training TreeTagger with a tailored label set.
• Comparison of performance with other tools (Stanza and UDpipe).
• Analyzing the impact of training data size on tagging precision.
• Proposing methods to better detect and categorize "that" in various linguistic contexts.

Implementation of a supermarket supply anticipation system based on sales

Sklearn, tensorflow, Keras, matplotlib,SQL

calculation of the probability of credit repayment

sklearn, seaborn, xgboost, lightgbm

Real-time customer unsubscription prediction

Kafka Stream, PySpark, Sklearn, Flask, Angular, Docker,SQL

Advanced Machine learning

Date of issue: 09/2022

Organism : Huawei

TensorFlow for Computer Vision

Date of issue: 10/2023

Organism : OpenCV University

GenAI for geospacial data

Date of issue: 10/2023

Organism : Nasa Space Challenge

Deep learning on Time series

Date of issue: 09/2023

Organism : Kaggle

Introduction to Deep learning

Date of issue: 10/2023

Organism : Kaggle