My main interest currently is the application of machine learning (Bayesian Optimization and Reinforcement Learning) for tuning and optimizing systems software, in particular, Linux sub-systems and compilers.
- Tuning NICs (Network cards): https://github.com/TreeinRandomForest/nic-tuning-experiments.
- Tuning gcc compiler parameters: https://github.com/TreeinRandomForest/gccoptim
- Code examples for Kubeflow book draft: https://github.com/TreeinRandomForest/kubeflow_usecases
- Short-course on ML for software engineers at Red Hat: https://github.com/TreeinRandomForest/BrnoMLWorkshop2019