Skip to content
View chaimae098's full-sized avatar

Highlights

  • Pro

Block or report chaimae098

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
chaimae098/README.md

Chaimae Kazoury

AI & Computer Science Engineering Student Β· ENSAM Casablanca

Typing SVG

LinkedIn Email Portfolio


About Me

I'm a 3rd-year Computer Science & AI Engineering student at ENSAM Casablanca. I build systems that catch anomalies in sensor streams, detect failures before they happen, and scale from raw data to live dashboards.

  • πŸ”­ Currently building Machine Failure Detection β€” industrial IoT end-to-end ML system
  • 🌱 Exploring time-series forecasting and geospatial data systems
  • πŸ… Oracle Certified Professional β€” Java SE 17 (2026)
  • πŸ’¬ Ask me about anomaly detection, sensor data pipelines, or Django + React stacks
  • πŸ“« chaimaekaz05@gmail.com

Featured Projects

Industrial IoT Β· Anomaly Detection Β· Full-Stack ML

Problem: Machines fail without warning β€” unplanned downtime is costly and avoidable.
Built: Full sensor data preprocessing pipeline β†’ supervised ML classifier β†’ Django REST API β†’ live React dashboard with real-time failure alerts.
Role: End-to-end β€” data pipeline, model training, backend API, and frontend dashboard.

Python Scikit-learn Django React PostgreSQL


Process Monitoring Β· Statistical Methods Β· Time-Series

Problem: Abnormal system behaviour hides silently in metric streams until it's too late.
Built: Time-series pipeline combining z-score, IQR, and rolling statistics to flag anomalies automatically. Reusable on any sensor or system stream.
Role: Designed the full detection pipeline and statistical method combination.

Python Pandas NumPy


NLP Β· Microservices Β· Full-Stack AI Β· Hackathon

Problem: IT teams waste hours every day manually triaging incident tickets.
Built: XGBoost + BERT embeddings for classification Β· FAISS semantic search over resolved incidents Β· FastAPI ML microservice Β· Django REST backend Β· React UI.
Role: Led the ML pipeline and semantic search component; integrated into the full-stack system.

Python FastAPI Django React


Tech Stack

AI & Data
Python Scikit-learn Pandas NumPy

Backend & APIs
Django FastAPI Spring Boot Laravel

Frontend
React JavaScript HTML5 CSS3

Databases & Tools
PostgreSQL MySQL Git Linux Postman


Experience

Web Development Intern Β· S B Solutions, Casablanca (Jan – Mar 2026)
Built a full-stack platform (React + Spring Boot) connecting clients with local service providers. Delivered features, participated in code reviews and sprint planning.

IT Intern Β· Fiscinfo, Casablanca (Jun – Aug 2025)
Analysed and validated internal system data. Collaborated across teams to improve data processing and reporting workflows.


Certifications

  • πŸ… Oracle Certified Professional β€” Java SE 17 Developer (2026)
  • ☁️ Oracle Cloud Infrastructure Foundations Associate (2025)
  • πŸ“Š Data Visualization β€” Kaggle
  • πŸ’» C Essentials 1 β€” Cisco

Pinned Loading

  1. Machine_failure_detection Machine_failure_detection Public

    Jupyter Notebook

  2. prmon-anomaly-detection prmon-anomaly-detection Public

    Jupyter Notebook