Hammouche Abdessamad
Verified Expert in Engineering
Data Scientist and Developer
Hammouche is a data scientist and deep learning engineer with over six years of experience designing machine learning models using computer vision and NLP. With a degree in applied mathematics, he can resolve complex business problems easily and efficiently. Hammouche developed the managerial skills to frame and carry out data projects with key account customers.
Portfolio
Experience
Availability
Preferred Environment
Python, Deep Learning, Machine Learning, Computer Vision, Azure, Google Cloud Platform (GCP), GPT, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), PySpark, Databricks, Microsoft Power BI
The most amazing...
...thing I've developed is a product that plugs into the surveillance camera system of malls to analyze videos and release customer KPIs.
Work Experience
Computer Vision Expert
Servier
- Identified important biomarkers for a rare brain disease using structural MRI to use them for a clinical trial.
- Designed and built a new MLOPS strategy using GCP services.
- Used state-of-the-art deep neural network models for brain MRI.
Data Scientist | Management Consultant
Capgemini
- Led a team of data scientists to implement an AI using computer vision to count the number of gas cylinders when a truck passed under a camera.
- Supervised five use cases as lead data science engineer to respond to several business issues.
- Collaborated with the chief data science engineer to study the state of the art of explainability algorithms. Built metrics to quantify the relevance of interpretability methods such as LIME, SHAP, ELI5, anchors, and counterfactual explanations.
- Led a team of data scientists to process 3D representations and detect specific objects in an airport.
Deep Learning Engineer
Digeiz
- Used neural networks while working on different computer vision problems such as segmentation, object localization, and crowd density estimation.
- Oversaw the neural network's optimization and acceleration in the graphic cards.
- Developed a tracking algorithm as multiple hypotheses tracking algorithm.
Deep Learning Engineer
BNP Paribas
- Replaced a model based on advanced feature engineering with a deep learning model for multi-label classification tasks.
- Added an explainability model to understand the prediction of recurrent neural network (RNN) and long short-term memory (LSTM).
- Presented the final work to an audience of over 50 business and technical people.
Experience
Crowd Density Estimation
Education
Master's Degree in Mathematics, Vision, and Learning
École Normale Supérieure - Paris, France
Engineer's Degree in Informatics and Applied Mathematics
Ecole Centrale Paris (CentraleSupelec) - Paris, France
Certifications
Azure Machine Learning
Microsoft
Skills
Libraries/APIs
TensorFlow, PyTorch, PySpark
Tools
Microsoft Power BI
Languages
Python, C++, C
Platforms
Azure, Databricks, NVIDIA CUDA, Google Cloud Platform (GCP)
Other
Deep Learning, Machine Learning, Computer Vision, Tracking, Object Detection, Classification, Explainable Artificial Intelligence (XAI), Recurrent Neural Networks (RNNs), Long Short-term Memory (LSTM), Artificial Intelligence (AI), Image Processing, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Videos, Reinforcement Learning, Clustering, Image Registration, Algorithms, MHT, Demand Sizing & Segmentation
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