Yiğitcan Baltacı
Machine Learning Engineer
I work on projects related to Machine Learning, Data Analysis, Natural Language Processing, and Computer Vision.
About Me
Hi! I'm Yiğitcan Baltacı, a 22-year-old Machine Learning Engineer based in İzmir, Turkey. I graduated from Konya Technical University, where I developed a strong foundation in computer engineering and data science.
With a passion for uncovering insights through data and building intelligent systems, I strive to merge innovation with practicality in everything I do. My journey into the world of machine learning began with a deep curiosity about how machines can learn, adapt, and transform industries. Since then, I've been honing my skills in data analysis, model development, and problem-solving.
When I'm not diving into algorithms or optimizing models, I enjoy exploring creative side projects, expanding my knowledge in artificial intelligence, and sharing what I've learned with others.
Welcome to my corner of the web. Let's connect and build something incredible together!
My Projects
Trendyol Review Analyzer
This project is a Python application that analyzes product reviews on Trendyol, providing users with statistical insights on product satisfaction and size recommendations
Trendyol Review Analyzer
The Trendyol Review Analyzer is a data analysis project that collects and processes product reviews from the Trendyol platform. The application uses web scraping to gather product reviews and provides statistical insights about product satisfaction and sizing information. This helps customers make more informed purchasing decisions by presenting review data in an easy-to-understand format.
Technologies Used
- Python
- Selenium(Web Scraping)
- Pandas,Numpy(Data Processing)
- Matplotlib(Data Visualization)
- Emoji(Data Cleaning)
Key Features
- Automatic review collection from Trendyol product pages
- Cleaning and organizing reviews
- Satisfaction analysis
- Size recommendation analysis
- Visual graphic reports
- User-friendly interface
Handwritten Digit Recognition
Deep Learning based handwritten digit recognition application with GUI interface.Users can draw digits on a canvas and get real-time predictions with confidence scores.
Handwritten Digit Recognition
A real-time handwritten digit recognition application powered by artificial intelligence. The model is trained on the MNIST dataset using TensorFlow and Keras, implementing a Convolutional Neural Network (CNN) architecture.
Technologies Used
- Python
- Deep Learning
- TensorFlow, Numpy, Pillow, Tkinter
- Convolutional Neural Networks (CNN)
Key Features
- Real-time digit recognition
- High accuracy predictions
- Confidence score display
- User-friendly graphical interface
Rubic Cube Solver
A desktop application that helps users solve a Rubik's Cube by scanning or manually inputting its colors and providing step-by-step solutions. Users can scan the cube's colors, adjust them manually, and receive solution steps. The application supports both a graphical interface and camera-based color detection.
Rubik Cube Solver
A desktop application that helps users solve a Rubik's Cube by scanning or manually inputting its colors and providing step-by-step solutions. Users can scan the cube's colors, adjust them manually, and receive solution steps. The application supports both a graphical interface and camera-based color detection.
Technologies Used
- Python
- OpenCV
- Numpy
- Tkinter
- Kociemba
Key Features
- Camera-based color detection: Scan the cube's faces using a camera.
- Manual color adjustment: Adjust the cube state manually through the interface.
- Solution calculation: Calculate solution steps based on the entered cube state.
- User-friendly interface: Provides a graphical interface using tkinter.
Your AI Assistant
A web application that extracts text from PDF documents, stores it in a PostgreSQL database, and allows users to interact with the content via an AI-powered chatbot. The app provides a seamless user experience with an intuitive interface.
Your AI Assistant
A web application that extracts text from PDF documents, stores it in a PostgreSQL database, and allows users to interact with the content via an AI-powered chatbot. The app provides a seamless user experience with an intuitive interface.
Technologies Used
- Python
- Flask
- SQLAlchemy
- PostgreSQL
- PyPDF2
- JavaScript
- HTML & CSS
Key Features
- PDF text extraction and storage.
- AI-powered chatbot for querying PDF content.
- PostgreSQL database for efficient data management.
- User-friendly chat interface.
Get in Touch
Feel free to reach out. I'll get back to you as soon as possible.
