Hi there! 👋 I'm Corentin, a Data Scientist passionate about extracting insights from data and leveraging it to solve real-world problems.
- 🔭 Currently exploring advanced techniques in Natural Language Processing (NLP) for text data analysis.
- 🌱 I’m constantly learning and experimenting with new tools and techniques in Data Science and Machine Learning.
- 💬 Ask me about anything related to Data Science, Machine Learning, or Python!
- Programming Languages: C, C++, Python, R, JavaScript, Java.
- Machine Learning & Deep Learning: TensorFlow, Scikit-Learn, PyTorch, YOLOv8.
- Natural Language Processing (NLP): NLTK, SpaCy.
- Big Data Technologies: Spark, Hadoop, DataBricks.
- Data Visualization: Matplotlib, Seaborn, Plotly, PowerBI, Adobe Illustrator, Adobe InDesign.
- Database Management: SQL (MySQL, PostgreSQL, SQL Server, SQLite), ETL.
- Version Control & Collaboration: GitHub, GitLab.
- Operating Systems: UNIX, MacOS, Windows.
- Cloud Platforms: Azure, AWS, GCP.
- Web Development: HTML/CSS, ReactJS.
- Microsoft Office Suite: Excel, PowerPoint, Word.
- Miscellaneous: PowerShell.
Here is a sneak peak of some of my personal Data Science projects:
- This NLP model categorizes UK political parties on a scale from left-wing to right-wing using speeches from MPs spanning 1970 to present.
- Technologies used: Python, NLP, Sentiment Analysis, TF-IDF, XGBoost.
- This project uses the YOLOv8 model to classify LEGO minifigure images, showcasing the power of deep learning in image recognition.
- Technologies used: Python, YOLOv8, Computer Vision.
- This project leverages satellite data and machine learning to predict rice crop locations in Vietnam's An Giang province, showcasing the fusion of remote sensing and data science.
- Technologies used: Python, Satellite Data, Random Forest, Deep Learning.
- Utilizing machine learning to classify RFID tags' movement, aiding in real-world asset tracking and theft prevention.
- Technologies used: Python, Random Forest, Feature Selection, Deep Learning.