Chapter 2: Generating Drum Sequences with the Drums RNN

1. Given a current sequence, predict the score for the next note, then do a prediction for each step you want to generate.

2. (1) RNNs operate on sequences of vectors, for the input and output, which is good for sequential data such as a music score, and (2) keep an internal state composed of the previous output steps, which is good for doing a prediction based on past inputs, not only the current input.
3. (1) First, the hidden layer will get h(t + 1), which is the output of the previous hidden layer, and (2) it will also receive x(t + 2), which is the input of the current step.
4. The number of bars generated will be 2 bars, or 32 steps, since we have 16 steps per bar. At 80 QPM, each step takes 0.1875 seconds, because you take the number of seconds in a minute, divide by the QPM, and divide by the number of steps per quarter: 60...