American Sign Language Action Recognition
Employment of MediaPipe and OpenCV for pose estimation.
About Me
As a marine biologist and data scientist, I am fueled by a passion for marine life and the transformative power of statistical analysis. My journey began with a love for exploring the wonders of the ocean and evolved into a fascination with harnessing the potential of data science to drive impactful decision-making in ecological studies. With a diverse skill set encompassing neural networks, machine learning, and data analysis, I am dedicated to leveraging data-driven approaches to address complex challenges in marine biology and beyond. My aspirations lie in using data science as a tool for informed decision-making, with the ultimate goal of contributing to the preservation and sustainability of our marine ecosystems. I thrive on approaching problems from multiple perspectives, meticulously examining each angle to identify the most effective solutions. One of my most memorable projects involved creating a model that recognizes American Sign Language signs for action recognition, utilizing a Long Short-Term Memory (LSTM) neural network. Continuously seeking to expand my knowledge and skills, I actively explore different models and techniques, embracing a mindset of lifelong learning and growth. Grounded in values of honesty and open communication, I believe in considering all possible angles of a situation to arrive at the optimal solution. Driven by a commitment to making a positive impact, I am dedicated to using my expertise in marine biology and data science to contribute to the betterment of our world, one data point at a time.
Recent Work
Heart Disease Predictor
Using dataset from CDC, we use various machine learning models and a forward-feed neural network to predict the risk of coronary heart disease.