Published inTowards Data ScienceClassification in the wildLet’s dive into classification metrics and discuss a few tricks, which could boost your classification pipeline performance.Nov 5, 2021Nov 5, 2021
Published inCatalyst TeamCatalyst 2021–Accelerated PyTorch 2.0In this post, I would like to share our Catalyst vision on Deep Learning R&D and show current development progress on various examples.Apr 19, 2021Apr 19, 2021
RL in RecSys, an overviewIn this review, I would like to show the scope of application of RL in RecSys and talk about the similarities between these two areas.Jan 17, 2021Jan 17, 2021
Published inPyTorchCatalyst dev blog - 20.07 releaseHi, I am Sergey, author of the Catalyst — PyTorch library for deep learning research and development. In our previous blogposts, we have…Jul 16, 2020Jul 16, 2020
Published inPyTorchCatalyst 101 — Accelerated PyTorchPyTorch is great framework to create deep learning models and pipelines. Nevertheless, for all its merits, it could use improvements in…Jun 2, 2020Jun 2, 2020
Run, skeleton, run!2 weeks ago, 13 November, one of the most exiting RL competitions of this year finally end. NIPS 2017: Learning to Run was really…Nov 27, 2017Nov 27, 2017
