enerative artificial intelligence (AI), focusing on its implementation using the C++ programming language. The text covers fundamental concepts, techniques, and practical applications of generative models, such as Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs). The sources also explain how to build neural networks, train deep learning models, and perform tasks related to natural language processing (NLP), such as text preprocessing and word embeddings. Finally, the sources explore advanced topics, including diffusion models, reinforcement learning, federated learning, and adversarial robustness
24 min