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This lecture covers tensor decomposition and Jennrich's theorem, focusing on tensor rank and the goal of decomposing tensors into terms of rank one. The slides discuss elementary bricks made out of vectors, tensor factorization, and tensor decomposition. The instructor explains the concept of tensor rank and the uniqueness of tensor decomposition. The lecture also touches on the notation used in tensor decomposition and the terminology related to polyadic decomposition. The presentation emphasizes the importance of understanding the spectral properties of tensors and the process of finding eigenvalues and eigenvectors.