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corentinbouton/README.md

Hi there! 👋 I'm Corentin, a Data Scientist passionate about extracting insights from data and leveraging it to solve real-world problems.

LinkedIn

About Me

  • 🔭 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!

Skills and Tools

  • 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.

Main Projects

Here is a sneak peak of some of my personal Data Science projects:

UK Politics: From Words to Votes

  • 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, Random Forest.

Political UK spectrum

LEGO Minifigures Classification

  • 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.

Predictions

EY Open Data Challenge 2023

  • 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.

Sample input satellite image         Test Confusion Matrix

RFID Tags Movement Detection

  • 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.

Experiment schema, data collection

Experiment schema, data collection

Pinned

  1. uk-politics uk-politics Public

    NLP model categorizing UK political parties on a scale from left-wing to right-wing using speeches from MPs spanning 1970 to present.

    Jupyter Notebook

  2. lego-minifigures lego-minifigures Public

    This project uses the YOLOv8 model to classify LEGO minifigure images, showcasing the power of deep learning in image recognition.

    Jupyter Notebook

  3. EY-open-data-challenge-2023 EY-open-data-challenge-2023 Public

    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.

    Jupyter Notebook

  4. RFID-tags-detection RFID-tags-detection Public

    Utilizing machine learning to classify RFID tags' movement, aiding in real-world asset tracking and theft prevention.

    Jupyter Notebook 1