About Laure
- Machine Learning and Deep Learning: sentiment analysis, prediction, classification, recommendation systems, intent engine, regardless of the data (Natural Language Processing, Computer Vision, or Timeseries), possibility of embedded systems. Transfer learning for deep learning (using pre-trained models). All with sklearn, pandas, openCV, gensim, Stanford CoreNLP, TensorFlow, Keras, or PyTorch.
- Relational database administration (SQL, Postgresql, etc.) or NoSQL like MongoDB (document storage), Neo4J (data graph storage)
- Data processing and analysis, structured or unstructured, regardless of input format (JSON, CSV, XLSX, or directly from a database) using data exploration techniques with pandas, numpy, etc.
- Automation and industrialization: Web scraping (BeautifulSoup, Selenium), using external APIs to retrieve information, generate documents, or trigger a script in response to an event (using the Google suite including emails, forms, sheets; Facebook, Twitter, ...), generating visualizations, Dashboards, and creating and maintaining SaaS (Software as a Service) APIs and applications (Flask, FastAPI, Django)
- DataOps / DevOps oriented Data: Deployment on your Linux servers or Cloud of scripts or databases. Containerization with Docker. CI/CD pipelines (Ansible, Heroku).
- Big Data and infrastructure management: Using cloud services with AWS ecosystems (IAM, S3, EC2, Lambda, API Gateway, Kinesis), Google Cloud Platform, Microsoft Azure, and Hadoop Spark, Kafka, etc. tools.
- Training and teaching technical subjects.
French
Native or bilingual
English
Native or bilingual
Experience
- ASSOCIATION LEONARD DE VINCIMachine & Deep Learning TeacherEDUCATION AND E-LEARNINGJanuary 2020 - Today (6 years and 5 months)Courbevoie, FranceTeaching 3 different courses: Data Analysis, Machine Learning, Deep Learning.Technologies used: Python, matplotlib, numpy, pandas, opencv, gensim, nltk, TensorFlow + Keras.Concepts worked on: Feature engineering, transfer learning, reinforcement learning, generative adversarial networks
- We Digital GardenData EngineerSOFTWARE PUBLISHINGJanuary 2019 - January 2021 (2 years and 1 month)Paris, France
- Various client-dependent missions: automation, data mining, creation of reports / insights from data.
- In parallel, creation of a full-stack web platform for User Intelligence Lab for data mining, integration, collection, analysis, and visualization.
Back-end: Python, Neo4J, Stanford Core NLP, and usual data processing libraries (numpy, pandas, nltk, scikit-learn, matplotlib, Flask, Selenium)Front-end: ReactJS.
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Education
- Computer Engineering DegreeEPITA2018Majeure SCIA