# krishnaik06/Interview-Prepartion-Data-Science

Repository: https://github.com/krishnaik06/Interview-Prepartion-Data-Science
Canonical: https://ross.abutalabs.com/products/interview-prepartion-data-science
Language: Jupyter Notebook
License Family: other
Last push: 2024-01-12T20:35:35+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2172, "days_push": 964, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1046, forks 676 (observed 2026-08-28T04:03:21.626734+00:00)

## What it is
A collection of Jupyter Notebook study materials for preparing for data science interviews. It covers common interview questions and concepts across data science, machine learning, and related topics.

## Use cases
- prepare for a data science interview
- review machine learning interview questions
- practice common data science concepts before an interview
- study statistics and ML theory for job interviews
- find example data science interview notebooks
- brush up on Python data science topics for interviews

## When to choose
- you are preparing for data science or ML interviews and want curated notebook-based study material
- you prefer learning through Jupyter Notebooks with worked examples
- you want a free community-maintained question bank for data science roles

## When to avoid
- you need a production library or tool rather than study material
- you need structured courses with assessments or certification
- you need up-to-date content guaranteed to reflect current interview trends, as updates are infrequent

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, developer-tools
- domain: data-science, education, machine-learning, tutorials
- platform: python, cross-platform
- tags: interview-preparation, jupyter-notebooks, data-science-interview, study-material, questions-and-answers

## Member repositories
- krishnaik06/Interview-Prepartion-Data-Science (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:21.626734+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:01:57.523405+00:00, confidence not recorded.
  - readme: https://github.com/krishnaik06/Interview-Prepartion-Data-Science (fetched 2026-08-28T04:03:21.626734+00:00, sha 6eacedf2379e)
- Data as of 2026-08-30T08:39:29.467469+00:00.