Akademik Veri Yönetim Sistemi
IEEE International Conference on Electrical, Computer and Energy Technologies, ICECET 2025, Paris, Fransa, 3 - 06 Temmuz 2025, (Tam Metin Bildiri)
The paper introduces an AI-powered web application designed to simplify machine learning for users with limited technical expertise. The platform automates the entire process, from data collection to model training and optimization. Using JSON-file techniques, users can effortlessly scrape web data and compile substantial image datasets. These datasets are preprocessed and fed into AutoKeras, an Automated Machine Learning (AutoML) library, which selects and fine-tunes the most accurate model. The optimized model is then made available for download directly from the platform, eliminating the need for expertise in dataset preparation, preprocessing, model training, or optimization.The web application features a user-friendly interface, with a frontend built using HTML and CSS and a backend powered by Python's Flask framework. By integrating automated web scraping, dataset creation, AutoML-driven optimization, and a streamlined interface, the platform enables non-technical users to create and deploy advanced AI models effortlessly. This innovative approach empowers users to explore AI applications, bringing powerful machine learning tools within reach for anyone, regardless of their technical background.