Kumparanian is a set of workflows that optimize Kumparan's data scientist hiring process. It cuts down 1-2 working day(s) submission review process to just less than an hour.
If you are our candidate, you need to install kumparanian
using following command
(we highly recommend to install inside virtual env, like venv):
python -m venv <your_env_name>
source <your_env_name>/bin/activate
pip install kumparanian
consult its help command:
% kumparanian ds --help
Usage: kumparanian ds [OPTIONS] COMMAND [ARGS]...
For Data Scientist role.
Before you submit your trained model, you can verify your trained model
using the following command:
$ kumparanian ds verify YOURMODEL.pickle YOURFILE.pickle
YOURMODEL.pickle should contain your trained model, and YOURFILE.pickle
should contain the necessary preprocessing components such as the vectorizer
and label encoder.
Use the following command to evaluate your trained model against your test
dataset:
$ kumparanian ds evaluate YOURMODEL.pickle YOURFILE.pickle test_file.csv
Options:
--help Show this message and exit.
Commands:
evaluate Evaluate the model
verify Verify the model
If you found any issues, feel free report it at:
https://github.com/kumparan/kumparanian/issues
then read our assessment and you should be good.
Subsequent sections are not required for candidate as it intended only for project's documentation purpose.
The first component of Kumparanian is a Kumparan's Model Interface. We've designed an interface for Machine Learning model that allows us to design a problem to have deterministic result.
The model interface contains 3 required methods: train
, predict
and
save
. The candidate will solve the assessment test by implement the train
and predict
methods. We provide save
method to helps the candidate to save
the trained model.
Read more about the Kumparan's Model Interface.
The second component of Kumparanian is a kumparanian
. This CLI will help
the candidate to verify and test their model while also help our team to evaluate
the candidate's trained model.
kumparanian
can be installed via the following command:
pip install kumparanian
To get started, run the following command:
kumparanian --help
If you found any issue, please open new issue here kumparanian/issues.