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 between words. Word embeddings are useful for tasks such as language translation, sentiment analysis, and document clustering.
Object Recognition is the capability of AI systems to identify and classify objects within images or videos. By utilising advanced algorithms and Neural Networks,…