Three principles of data science: predictability, computability, and stability (PCS)

Bin Yu; Karl Kumbier

doi:10.5281/zenodo.3522419

Published October 11, 2018 | Version v2

Dataset Open

Three principles of data science: predictability, computability, and stability (PCS)

Bin Yu¹
Karl Kumbier¹

1. UC Berkeley

This repository contains the data, codes, and PCS documentation described in: Three principles of data science: predictability, computability, and stability (PCS).

Files

pcs_analyses.zip

Files (2.9 GB)

Name	Size	Download all
pcs_analyses.zip md5:35a6784f2f4d763422853ce0b31f5aa0	2.9 GB	Preview Download

Views

Downloads

Show more details

	All versions	This version
Views	2,667	1,547
Downloads	1,036	838
Data volume	7.2 TB	7.2 TB

More info on how stats are collected....

DOI

Resource type

Dataset

Publisher

Zenodo

Creative Commons Attribution 4.0 International

The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more

Technical metadata

Created: November 7, 2019
Modified: January 24, 2020

Three principles of data science: predictability, computability, and stability (PCS)

Creators

Description

Files

pcs_analyses.zip

Files (2.9 GB)