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.