• Used Technologies: Python, Pandas, NumPy, Scikit-learn, LGBM Ranker, SQL,Matplotlib, Scikit-learn Jupyter Notebooks.
• This project involves building a personalized recommendation system for LC Waikiki's e-commerce platform using the LGBM ranker algorithm. By analyzing customer shopping data, the system provides tailored product suggestions, enhancing the user experience and driving sales through relevant recommendations. 🛒🔍

• Used Technologies: Python, YOLO, OpenCV, TensorFlow, Jupyter Notebooks.
• This project focuses on microtrend analysis to evaluate how well LC Waikiki captures emerging fashion trends. Collaborating with a team member from LC Waikiki, I worked on the clothing detection aspect using video data. For this, I fine-tuned pre-trained YOLO models to accurately identify trending apparel in videos. The insights from this project help LC Waikiki assess and adapt to current fashion trends more effectively, enhancing their product offerings and market competitiveness. 👗📊

• Used Technologies: Python, FastAPI, Streamlit, Pandas, Email Parser Library.
• This project involves developing a mail parsing tool for LC Waikiki to automate data extraction from .msg files. I created a Python API using FastAPI to parse emails, extracting key information and exporting it to Excel format. The project also includes a user-friendly interface built with Streamlit, making it easy for users to interact with the tool. This solution is currently used by the department, significantly reducing manual workload and streamlining the data processing workflow. 📧🔍📊

• Used Technologies: Python, Flask, Streamlit, Scikit-learn, Pandas.
• This project revolves around developing a clustering solution for LC Waikiki, designed to meet departmental needs through optimized code execution. I built a Flask API to streamline clustering processes, allowing the department to run required analyses efficiently. Additionally, I created a user-friendly interface with Streamlit, enabling easy interaction with the API. This application helps the team perform clustering tasks with improved performance and accessibility, ultimately enhancing their data-driven decision-making processes. 📊🛠️

• Used Technologies: Python, PyTorch, Google Colab, Jupyter Notebooks.
• This project involves developing a machine learning model to quickly assess milk quality, focusing on preventing overfitting through early stopping. By analyzing key factors like pH and temperature, a deep neural network classifies milk into three quality levels with 91.04% accuracy on the test set. The project emphasizes efficient development and aims to improve food safety, reduce waste, and optimize dairy production using an IoT dataset for real-time quality predictions. 🥛🔍🤖

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• Used Technologies: Arduino, MQ-135 Air Sensor, Python, Online Dashboard.
• This project aligns with the 4th Sustainable Development Goal by introducing an automated ventilation system to improve classroom air quality, thus enhancing the learning environment. Utilizing an MQ-135 air sensor and Arduino, the system monitors CO2 levels and activates ventilation when thresholds are exceeded, with fan speed dynamically adjusted based on real-time data. The setup is accessible online, and future enhancements include integrating machine learning for optimized responses. Inspired by Bogdanovica et al.'s study on CO2's impact on student well-being, this project aims to create healthier, more productive educational spaces. 🌍🏫🔧

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• Used Technologies: Python, Pandas,NumPy,Scikit-learn, Matplotlib Apriori Algorithm, SQL.
• This project analyzes sales data from an LC Waikiki store covering January 1, 2019, to December 31, 2019, with a dataset of 2,122,720 records. By examining this data, the project aims to understand customer shopping behavior and preferences. Utilizing the Apriori algorithm, it suggests additional products based on items added to customers' carts. With around two million data points, this application provides valuable insights into potential purchases, helping to enhance the customer experience and optimize sales strategies. 🛍️📈

• Used Technologies: JavaScript, React.js, Ant Design, Yarn.
• Developed for Mazaka Yazılım, this project utilizes JavaScript, React.js, Ant Design, and yarn packages to create a user-friendly website aimed at efficiently managing and updating instructional materials for the company's customers. The system allows customers to actively engage with instructional content through an admin panel, enabling them to upload and update written documents seamlessly. By providing a platform for easy access and management of instructional materials, this project enhances customer experience and streamlines communication between Mazaka Yazılım and its clientele. 🌐📝

"Petal to Future" is a Flutter app designed for sustainable transportation, utilizing Firebase for seamless functionality. With features like step counting via Google Fit, carbon footprint calculation, and Google Maps integration, the app encourages eco-friendly commuting. Users earn points based on their eco-conscious choices, contributing to a leaderboard and offering chances to win prizes. The project not only prioritizes green commuting but also serves as an ideal Flutter application for those seeking a comprehensive introduction to mobile development. Don't forget to ⭐ star the repo to show support! 🌍📱

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"Take Care of You" is experience tranquility with MindfulMood, a Flutter meditation app powered by Firebase. Enjoy a serene splash screen, easy sign-in, and soothing meditation tracks. Enhancements include heart rate measurement, journaling, motivational notifications, and security features like fingerprint authentication. Elevate your mindfulness journey with MindfulMood. ⭐️🧘‍♀️

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Crafted with Flutter, Dart, Google Firebase, and leveraging Agile methodology, this application serves the purpose of introducing AGU Youth Factory to students at Abdullah Gül University. The primary goal is to foster seamless communication between students and the Youth Factory. By utilizing cutting-edge technology and an agile approach, the app provides an engaging platform for students to connect with the Youth Factory, enhancing their awareness and interaction. 🚀📚

Embark on a green journey with Planty, a cutting-edge Flutter project designed to bridge the gap between producers and consumers in sustainable agriculture. Fueled by Firebase, this mobile app offers a user-friendly experience, empowering producers with insights into sustainable farming while creating direct interactions with consumers. With streamlined processes for buying and selling organic products, an interactive forum page, and a search feature for specific sustainable farming methods, Planty is set to make organic goodness easily accessible to everyone. Dive into sustainable agriculture practices with Planty—where producers and consumers thrive together! 🌍📱

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Task Manager is a web application developed with React and TypeScript, integrated with JSONPlaceholder's to-do list API. Offering features like task listing, addition, and user sharing, the app provides a user-friendly interface with a clear and modern design. The frontend utilizes React, TypeScript, Styled Components, and React Query, while the backend relies on the JSONPlaceholder REST API for tasks and users. Installation is straightforward, and the app promises a seamless experience for managing personal or work-related tasks. 🚀📝

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