Agile Development of Deep Learning Applications

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.