Data-science-development-project-template Alternatives

Similar projects and alternatives to data-science-development-project-template

dvc

109 13,139 9.6 Python data-science-development-project-template VS dvc

🦉 ML Experiments and Data Management with Git
workflowr

2 807 5.4 R data-science-development-project-template VS workflowr

Organize your project into a research website
InfluxDB

www.influxdata.com featured

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
projects

2 6 3.6 Jupyter Notebook data-science-development-project-template VS projects

Various research projects (by jolespin)

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better data-science-development-project-template alternative or higher similarity.

Suggest an alternative to data-science-development-project-template

data-science-development-project-template reviews and mentions

Posts with mentions or reviews of data-science-development-project-template. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-17.

How do you manage results, plots, etc.?
4 projects | /r/bioinformatics | 17 Nov 2022

Bioinf has a lot of biologists who have transitioned into more technical/coding focused roles, so you'll find there's not a lot of engineering workflow standards out there compared to DS or SWE. As others have said, snakemake is the most common, but thats just a pipeline managment tool, it doesn't manage data or outputs. I personally use DVC for data and pipeline management (and include jupyter and papermill to make it all work), although I haven't yet gotten onboard with their experiments feature (which is what would manage different parameters and figures/results beyond versioning). I looked into MLflow and some other options when I was getting started (I do tool development and bioinf analysis), but I wanted data versioning to ensure experiment reproducibility (kind of a critcal part of science IMO), and many of the other solutions like Airflow (common in DS industry) seemed to be overkill for smaller bioinfo projects. DVC meets the requirements and I like it in concept, although in practice there have been many updates that have been a bit of a pain to keep up with/integrate. I've got a bioinfo/ds project template on github that roles together git, conda, DVC, jupyter and papermill to ensure experiment reproducibility, and is setup as a template that can be deployed with cookiecutter - check it out if you like.