Embedding problem

In the context of machine learning and natural language processing, the term "embedding problem" can refer to several related concepts, primarily revolving around the challenge of representing complex data in a form that can be effectively processed by algorithms. Here are some key aspects: 1. **Embedding Vectors**: In machine learning, "embedding" typically refers to the transformation of high-dimensional data into a lower-dimensional vector space. This is crucial for enabling efficient computation and understanding relationships between data points.