Further reading
For those interested in diving deeper into some of the techniques mentioned in this chapter, here are some recommendations that should help you understand the basics.
One of the most interesting and challenging frameworks we have discussed is tensor networks. Many resources can be found in the literature. Still, two that we can recommend are the work by Biamonte and Bergholm from 2017, which provides a solid foundation to understand its potential better. For those more hands-on engineers, the Quimb (Gray, 2018) and Jet (Vincent et al., 2022) Python packages provide a fun way to learn and experiment.
Similarly, distributed computation has a path, and works by Zaharia et al. (2010) on Apache Spark and Moritz et al. (2018) on Ray are leading the path toward easy-to-implement distributed solutions.
Something particularly interesting is the contribution of the Baidu team to the existing PaddlePaddle framework (Ma et al., 2020). Not only have they provided an industrial...
