Hyperparameters are parameters that are set before the training of an AI model. They control the behaviour and performance of the model, such as learning rate, batch size, and regularisation strength. Selecting appropriate Hyperparameters is crucial for optimising model performance and improving accuracy.
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…