My name is Yuval Argoetti, and I am a highly motivated and enthusiastic biomedical engineer.
My goal in studying engineering is to gain knowledge in a variety of engineering fields, ranging from electronics and machine learning to data science, programming, physiology, mechanics, robotics, and beyond. I am passionate about exploring and developing new and exciting technologies that have the potential to make a positive impact in the world. Throughout my academic journey, I have acquired a diverse skill set.
I am enthusiastic about utilizing these tools to solve real-world problems and contribute to advancements in various industries.
Believing in the power of hard work and continuous learning, I am constantly seeking opportunities to expand my abilities and acquire new skills.
During my education, I specialized in Machine & Deep Learning, Signal & Image Processing, and Robotics. I have gained valuable theoretical knowledge and practical skills in these areas, which have contributed to my proficiency in various technical domains.
I have a keen interest in the following fields:
- Deep Learning
- Machine Learning
- Data Science
- Big Data
- Computer Vision
- Signal Processing
- Robotics
I possess technical skills in the following areas:
- Python
- PyTorch
- OpenCV
- MATLAB
- Deep Learning
- Machine Learning
- Signal Processing
- Image & Video Processing
- System Integration
- Engineering Design
- Risk Management
In addition to my formal education, I have self-taught SOLIDWORKS, C++, and Arduino.
The repositories showcase severals of my projects in various subjects, including deep learning, machine learning, robotics, data science, signal processing, image processing, graphical user interface (GUI) applications, object-oriented programming (OOP), algorithms, and more.
The projects cover a wide range of topics and application. The folder structure is designed to provide easy navigation and access to project details.
Within each project folder, you will find a readme.md file that provides details about the corresponding project.
Feel free to explore each project folder to gain a deeper understanding of the subjects covered and the technical implementations. If you have any questions or would like further information, please don't hesitate to contact me.
During my academic journey, I have undertaken several deep learning and machine learning projects, including:
- Created and trained PyTorch neural network models, such as Transformer for NLP and CNN for image classification. These projects showcase my knowledge in deep learning and hands-on implementation.
- Developed continuous monitoring systems involving data collection, sampling, filtering, feature extraction, feature selection, and classification. Notable projects in this domain include hand gesture prediction using gyroscope and accelerometer data from a wearable device and an activity prediction system utilizing data from multiple sensors of smartphones.
Designed and developed a device that converts visual feedback to auditory feedback for home appliances, enabling visually impaired individuals to receive real-time program updates. Project included Arduino & C++ programming, 3D printing, design, and assembly of electrical circuits & sensors.
Guitars 🎸, Music 🎵, Gaming 🎮, Traveling 🌍✈🧭, Trekking 🥾🧗🏔️🏕️
Tel Aviv, Israel
Feel free to reach out to me via email or through GitHub if you have any questions, collaborations, or opportunities. I am open to connecting and exploring new possibilities.
Thank you for visiting my GitHub profile and considering my work.
Yuval Argoetti.