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.
A convolutional neural network is a powerful deep learning model designed for processing and analysing visual data. It excels in tasks such as image…