I am following the tutorial about Time Series from the official documentation of Tensorflow (Time series forecasting  |  TensorFlow Core 6)
Very early in the tutorial they transform the datetime to Sine and Cosine signals to help train the model. This signals are created using the number of seconds in a day and year. They then explain that it can be checked using a FFT function. In the graph that is generated there are clear peaks on “1/year” and “1/day”. I guess this is the reason they used this timelapses to create the Sine and Cosine columns.
In a classic FFT, the Y axis usually represents the amplitude of a sound, for instance. My question relies on what this stands for in terms of time and why the peaks are the values chosen for the sine and cosine columns.