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Data Scientist with a strong background in machine learning, computer vision, and application development. As a final-year engineering student specializing in data science and artificial intelligence
I have worked on innovative projects that leverage cutting-edge technologies to solve complex problems.
Hi! My name is Elliot Bouchy, and I’m a Data Scientist with a passion for solving complex problems using machine learning, computer vision, and data-driven solutions.
I enjoy transforming raw data into actionable insights, leveraging tools like SQL, Microsoft Azure, and Python. My approach emphasizes curiosity, critical thinking, and collaboration to deliver high-quality results. Outside of work, I’m passionate about sports, reading, and exploring new technologies.
Whether it’s building predictive models or optimizing systems, I’m always eager to contribute to ambitious projects that push technological boundaries.
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python
SQL
spark
docker
tensorflow
aws
sckitlearn
numpy
GITHUB
GIT
EmotionDetect: A groundbreaking project that leverages advanced machine learning and computer vision techniques to analyze subtle facial micro-expressions. This system is designed to detect and classify emotions by processing event-based camera data, offering a new perspective on human emotional analysis.
ChessVision VR: An innovative project that combines computer vision and virtual reality to identify unknown chess pieces and provide real-time feedback to users. Designed to enhance the chess-playing experience, this system integrates advanced image recognition algorithms with a VR headset to deliver immersive and interactive gameplay.
Hold the Line: A pioneering system designed to assist visually impaired individuals in navigating obstacle courses using computer vision and audio guidance. This project combines innovative algorithms with hardware solutions to provide real-time spatial feedback through headphones.
SentimentDetect: Pushing the Boundaries of Sentiment Analysis with AI Discover EmotionDetect, an innovative project that leverages advanced AI techniques to analyze sentiments in social media text. By comparing state-of-the-art models like BERT with traditional approaches (TextBlob, VADER), this project demonstrates the power of deep learning in understanding emotional nuances in online conversations.
AudioGuardian: Revolutionizing Industrial Sound Anomaly Detection with AI Explore AudioGuardian, an innovative project that harnesses cutting-edge AI techniques to detect anomalous sounds in industrial environments. By comparing advanced deep learning models like Variational Autoencoders (VAEs) with traditional Autoencoders (AEs), this project showcases the power of probabilistic approaches in identifying subtle audio irregularities.
Explore Aerial Cactus Identifier, a project that leverages custom-designed convolutional neural networks to detect cacti in aerial imagery. By combining deep learning techniques with data augmentation strategies, this project achieves a good accuracy in challenging real-world conditions.
