08 · Recursion with Matrices and Vectors
Part IV demo of Tensors for Machine Learning. One simple pattern:
Use the current state to create the next state, then repeat.
The same pattern appears in Fibonacci numbers, in power iteration, and in a real monthly airline-passenger forecast. The last of those combines recursion with the pseudoinverse from section 07 — fit a model that predicts each month from the previous 12, then apply it to its own output.
This is exactly the structure of a recurrent neural network: a hidden state, updated by the same weights at every step.
Study here, then run the real thing: notebook 08 on Colab · the handbook · workshop home
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