Agile Development of Deep Learning Applications - Dvorzhak, Valentina;Tomka, Yurii;Talakh, Maria
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This monograph showcases agile development of deep learning applications, focusing on recommendation systems. It presents projects in diverse contexts: personalized music playlists via text sentiment analysis, a knowledge-sharing platform using graph neural networks, automated IT specialist selection with graph autoencoders, and a creative writing platform with recommendations. It emphasizes modern techniques (NLP, GNN) and microservice architecture. The work highlights agile methodologies, iterative development, and business analysis (ML Canvas). Practical cases demonstrate enhanced user…mehr

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Produktbeschreibung
This monograph showcases agile development of deep learning applications, focusing on recommendation systems. It presents projects in diverse contexts: personalized music playlists via text sentiment analysis, a knowledge-sharing platform using graph neural networks, automated IT specialist selection with graph autoencoders, and a creative writing platform with recommendations. It emphasizes modern techniques (NLP, GNN) and microservice architecture. The work highlights agile methodologies, iterative development, and business analysis (ML Canvas). Practical cases demonstrate enhanced user experience, improved enterprise efficiency, and innovative tools.
Autorenporträt
Valentyna Dvorzhak is an Assistant Professor of the Computer Science Department. Her scientific interests include: Computer Vision, Deep Learning, Machine Learning, Business Analysis, and Project Management for the Development of Intelligent Applications.