Catalyst is PyTorch framework for Deep Learning research and development. You get a training loop with metrics, model checkpointing, advanced logging and distributed training support without the boilerplate.
Catalyst.Team and Catalyst.Contributors consist of industrial and academia researches, kaggle masters and professional software engineers. You can check out Catalyst-based kaggle competitions, pipelines and projects here.
Catalyst was designed by researchers for researchers,
to get the foundation for DL & RL research, which would be well tested and verified
to generalize and develop best practices that work with all DL areas
to think less about tech-side and focus on research hypothesis and their value
to accelerate your research
combines research best practices and helps knowledge sharing
connects DL/RL with Software Engineer for maximum performance
allows quickly and efficiently validate your hypotheses
Catalyst main principles,
open — it’s fully Open Source Ecosystem
equivalently — everyone can contribute and propose new ideas
expertise — we are gathering top deep learning knowledge into one place
high-performance — we are developing the ecosystem with software engineering best practices
Open Source Research Community
Last but not least, Catalyst.Friends community connects different startups, companies and research labs all over the world. For example, Catalyst.Team is working with Translational Research in Neuroimaging and Data Science (TReNDS) on DL brain image analysis. Feel free to write us, if you are also interested in such collaborations.