We present an open source library to shrink pickled scikit-learn and lightgbm models. We will provide insights of how pickling ML models work and how to improve the disk representation. With this approach, we can reduce the deployment size of machine learning applications up to 6x.
Pavel is a data engineer at QuantCo who is currently studying Mathematics and Computer Science at KIT.
Yasin works as a Data Engineer at QuantCo and studies Computer Science at Karlsruhe Institute of Technology (KIT)
visit the speaker at: Github