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.
Time Series Analysis is an AI technique that analyses data points collected over time. This approach involves detecting trends, patterns, and seasonality in the…