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Xinfra Monitor monitors the availability of Kafka clusters by producing synthetic workloads using end-to-end pipelines to obtain derived vital statistics - E2E latency, service produce/consume availability, offsets commit availability & latency, message loss rate and more.
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
PeTar is a high-performance N-body code for modelling the evolution of star clusters and tidal streams, including the effect of galactic potential, dynamics of binary and hierarchical system, single and binary stellar evolution.