data-science-best-practices
The goal of this repository is to enable data scientists and ML engineers to develop data science use cases and making it ready for production use. This means focusing on the versioning, scalability, monitoring and engineering of the solution.
How to download and setup data-science-best-practices
Open terminal and run command
git clone https://github.com/IBM/data-science-best-practices.git
git clone is used to create a copy or clone of data-science-best-practices repositories.
You pass git clone a repository URL. it supports a few different network protocols and corresponding URL formats.
Also you may download zip file with data-science-best-practices https://github.com/IBM/data-science-best-practices/archive/master.zip
Or simply clone data-science-best-practices with SSH
[email protected]:IBM/data-science-best-practices.git
If you have some problems with data-science-best-practices
You may open issue on data-science-best-practices support forum (system) here: https://github.com/IBM/data-science-best-practices/issuesSimilar to data-science-best-practices repositories
Here you may see data-science-best-practices alternatives and analogs
httpie chef awesome-computer-science-opportunities grafana matomo telegram-list netdata jenkins stats docker_practice gitea dashboards awesome-datascience papers-I-read react-native-firebase portal kong openebs metabase wtf goaccess lynis metrica-sdk-ios adminset owl laravel-server-monitor webterminal urlooker redash laravel-backup