Make your data science workflow efficient and reproducible with MLflow

added by DotNetKicks
6/13/2019 9:09:24 PM

1 Kicks, 193 Views

When data scientists work on building a machine learning model, their experimentation often produces lots of metadata: metrics of models you tested, actual model files, as well as artifacts such as plots or log files. They often try different models and parameters, for example random forests o...