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.
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