TensorLy is a python library that provides a high level API for tensor methods and deep tensorized architectures. Tensor methods are natural extensions of traditional matrix algebraic methods to higher orders. While they have been extensively used in fields such as quantum systems, signal processing and psychometrics, they only recently started to be employed in Machine Learning. They have the potential to both help us develop better theory about deep learning, and to leverage the multi-dimensional structure in the data. After a short introduction to tensor methods, I will present some way in which tensor methods can be combined with deep learning, and demonstrate through Jupyter notebooks on how easy it is specify tensorized neural networks.