Designing AI products that are fast, reliable, and intuitive to use.
class Kamal_Dehbi:
def __init__(self):
self.name = "Kamal Dehbi"
self.role = "Data Scientist & AI Engineer"
self.education = "ENSAM Rabat, Morocco - Data Science & AI"
self.location = "Rabat, Morocco"
self.interests = ["Machine Learning", "Computer Vision", "NLP", "Data Platforms", "Product Design", "LLM", "RAG"]
def get_stats(self):
return {
"ai_ml_projects": "10+",
"technologies": "30+",
"experience_years": "3+",
}
def current_focus(self):
return [
"Operationalizing deep learning models : CV & NLP",
"LLM + RAG workflows for multilingual data",
"Streaming analytics with Kafka",
"Bulletproof MLOps & deployment"
]Available for: Internships | Freelancing | Collaborations
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Comprehensive web application to track and manage watched content with integrated rating system, user reviews, and personalized recommendation engine.
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ESP32-based IoT system with ultrasonic sensors, LED indicators, MQTT publishing, and real-time React dashboard for parking spot monitoring.
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Music + moderation assistant with slash commands, queueing logic, and live event telemetry.
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Automation-first crawler batches chapter downloads, optimizes image payloads, and cleans metadata.
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Tools and technologies I rely on daily.
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Python |
Java |
C |
C++ |
R |
MATLAB |
Scala |
HTML5 |
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CSS3 |
JavaScript |
TypeScript |
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TensorFlow |
PyTorch |
OpenCV |
scikit-learn |
Keras |
XGBoost |
spaCy |
LangChain |
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YOLO |
Hugging Face |
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Pandas |
NumPy |
Matplotlib |
Seaborn |
Plotly |
Power BI |
Looker Studio |
SciPy |
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Kafka |
Hadoop |
Hive |
Sqoop |
Spark |
HBase |
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React |
Flask |
FastAPI |
Node.js |
Bootstrap |
Jinja |
Selenium |
Java EE |
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Streamlit |
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PostgreSQL |
MySQL |
SQLite |
Oracle SQL |
MongoDB |
Neo4j |
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Git |
GitHub |
Linux |
Docker |
VS Code |
AWS |
Jenkins |
MLflow |
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Jupyter |
Activity snapshots, skill spread, and contribution highlights.