Jérémie Guilherme

Passionate about Machine Learning and sports, I assist companies, startups, and sports clubs in data exploitation and the creation of AI-based solutions. My expertise primarily focuses on Natural Language Processing (LLMs, chatbots, AI assistants) and Computer Vision, but my passion for sports has also led me to develop advanced skills in sports data analysis.

Machine Learning:

- Training of supervised and unsupervised models

- Optimization of ML pipelines for real-world use cases (NLP, vision, sports)

- Evaluation, deployment, and performance monitoring of models

AI Development:

- Design of personalized chatbots

- Development of tailor-made AI solutions (AI assistants, planners, etc.)

- Training and deployment of Computer Vision models (Detection, Classification, Tracking).

Data Science applied to Football:

- Creation of detailed scouting reports

- Development of xG (expected goals) models

- Implementation of advanced KPIs for tactical analysis.

Data Engineering & Cloud:

- Database management (MongoDB, MySQL, PostgreSQL, Redis, SQLite)

- Deployment on AWS

- Development of scalable backends and APIs (FastAPI)

Languages: Python, JavaScript

Data Manipulation & Analysis: Pandas, NumPy

Data Visualization: Matplotlib, Seaborn

Machine Learning Modeling: Scikit-Learn

Databases: PostgreSQL, MySQL, SQLite, MongoDB, Redis

Fine-tuning and Training: PyTorch, TensorFlow, Keras

NLP: Hugging Face Transformers, LangChain, CrewAI, OpenAI, LLaMA, Mistral, Anthropic

Image Detection and Segmentation: YOLOv10, DINOv2, U-Net

Image Processing: OpenCV

Object Tracking: DeepSORT, SORT, ByteTrack

Football Data Sources: StatsBomb, Opta, Wyscout

Cloud Platforms: AWS (S3, Lambda, SageMaker, EC2)

Frontend: React.js, Next.js

Backend: FastAPI, Django