Learn about training data, its types, and its crucial role in machine learning. Discover the differences between training and testing data, and the importance of data quality for model performance.
Explore the concept of Deep Belief Networks, their historical significance, and why they've been largely replaced by more advanced neural network architectures.
Dive into the world of Generative Adversarial Networks (GANs). Learn how these powerful AI models work, their applications, and the different types of GANs.
Quantum generative models use quantum mechanics to create complex data, offering efficiency and novel insights but facing hardware and algorithmic limitations.
