Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new data samples similar to the training data. They have applications in tasks such as image generation, anomaly detection, and data compression.
Word Embeddings are a technique in NLP that represent words as continuous vectors in a high-dimensional space. These vectors capture semantic and syntactic relationships…