This appendix gives a brief overview and glossary of technical concepts used throughout the book.
Amdahl's law predicts the maximum possible speedup due to parallelization. The number of processes limits the absolute maximum speedup. Some parts of any given Python code might be impossible to parallelize. We also have to take into account overhead from parallelization setup and related interprocess communication. Amdahl's law states that there is a linear relationship between the inverse of the speedup, the inverse of the number of processes, and the portion of the code that cannot be parallelized.
ARMA models combine autoregressive and moving average models. They are used to forecast future values of time series.