Hello! 👋🏻 I'm Aliaksandra, but feel free to call me Sasha. My coding projects are influenced by my life experiences, where I unite the realms of art, technology, and physics. During my formative years, I actively engaged in math Olympiads and art competitions, experiences that gave me a profound understanding of the synergy between science and art.
Pursuing BSc in Computer Science at Polish-Japanese Academy of Information Technology • Warsaw, Poland
Space Hackathon by Alpha XR crew PJAIT 2022 • 3rd place with 'Duck Space Crew Assistant' project by the Yoda team
Open-Source Contributor at Zero-to-Mastery Academy
International Children Painting Competition in Hong Kong 12-13, Country Representative (Participant Number: #1)
Tech Skills
my_information = {
"Research": "🎓 Conducting research on AI and Computer Vision",
"Collaborations": "💡 Open to collaborating on coding projects",
"Current Work": "💻 Currently working on Remote Sensing",
"Dev Experience": "👾 WordPress Developer & Search Engine Optimization Specialist @ Synder (YCombinator Summer21 FinTech App)",
}
technologies_i_work_with = {
"Languages": ["Python", "C++"],
"ML Libraries": ["Pandas", "NumPy", "PyTorch", "TensorFlow",
"Matplotlib", "Scikit-Learn"],
"Cloud Platforms": ["AWS", "Google Cloud"],
"CI/CD": ["Jenkins", "Gitlab"],
"Containers": ["Docker", "Kubernetes"],
"Computer Graphics Tools": ["Blender", "Unreal Engine"],
"Other": ["Linux", "Kali Linux", "Bash", "Git"],
}
print("My Information:")
for key, value in my_information.items():
print(f"{key}: {value}")
print("\nTechnologies I work with:")
for key, value in technologies_i_work_with.items():
if isinstance(value, list):
value_str = ", ".join(value)
else:
value_str = value
print(f"{key}: {value_str}")
Coding Projects
ML Picture Classificator
tech: Python3, TensorFlow 2.0, Jupyter Notebook, ML libraries
The project utilizes transfer learning and TensorFlow 2.0 framework to train a model capable of classifying over 100 different dog breeds. By leveraging the knowledge of a pre-trained model, the project achieved accurate image classification by fine-tuning the model on a specific dataset.
Network Visualization
tech: Python3, D3.js, SQLite
This project demonstrates how to visualize networks and interconnections using the D3.js (Data-Driven Documents) visualization library. The code is written in Python and SQLite for data preparation and management, and the resulting data is used to generate interactive network visualizations using D3.js.
API YouTube App
tech: Python3, GET Requests, Macros, Markup Filters
Built using Python, the web application fetches data from the YouTube API and displays it in an easy-to-use and user-friendly format.
C++ Image Processing Library
tech: C++, CMake
This C++ library performs various image processing tasks based on universal and specific C++ programming practices. The library includes features such as 2-D discrete convolution and correlation, edge detection, filter algorithms, image histogram and equalization, gray-level transformation, and enhancement of image quality.
tech: Python3, ML libraries
A dataset encompassing various health attributes and medical history, with the goal of creating a predictive model that can identify individuals at risk of heart disease. The project aims to enhance healthcare outcomes by providing timely insights for preventive care and intervention.
Market Price Prediction
tech: Python3, ML libraries
This machine learning project is focused on predicting the sale prices of trucks through the application of advanced algorithms. It leverages a comprehensive dataset that includes key attributes of the trucks, such as mileage, make, model, and year of manufacture.
Cars and Pedestrians Tracking
tech: Python3, OpenCV library
Simple Python application for detecting and tracking cars and pedestrians in videos using OpenCV. The application uses a pre-trained object detection model from OpenCV.