# khanhnamle1994/cracking-the-data-science-interview

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

Repository: https://github.com/khanhnamle1994/cracking-the-data-science-interview
Canonical: https://ross.abutalabs.com/products/cracking-the-data-science-interview
Homepage: https://medium.com/cracking-the-data-science-interview
Language: Jupyter Notebook
License Family: other
Topics: data-science, machine-learning, deep-learning, data-portfolio, downloadable-cheatsheets, statistics, python, data-journalism, concepts, data-wrangling
Last push: 2024-08-31T11:22:32+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2946, "days_push": 732, "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 4743, forks 1211 (observed 2026-08-28T04:08:57.828125+00:00)

## What it is
A curated collection of cheatsheets, ebooks, interview questions, case studies, and portfolio projects for data science and machine learning interview preparation. It is a learning resource repository rather than runnable software.

## Use cases
- prepare for a data science interview
- find machine learning interview questions and answers
- review statistics and probability concepts before an interview
- get downloadable cheatsheets for SQL and ML topics
- build a data science portfolio with example projects
- study deep learning and NLP concepts for job interviews

## When to choose
- you are preparing for data science, ML, or analytics interviews
- you want condensed cheatsheets and curated reading material in one place
- you need example portfolio projects to showcase data skills

## When to avoid
- you need production code, libraries, or tools to include in a project
- you want a structured interactive course with exercises and grading
- you need up-to-date material, as some content may be dated

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, machine-learning, deep-learning
- domain: data-science, machine-learning, tutorials, education
- platform: python
- tags: interview-preparation, cheatsheets, ebooks, question-bank, portfolio, statistics, sql

## Member repositories
- khanhnamle1994/cracking-the-data-science-interview (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:57.828125+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 2026-08-29T18:18:57.028981+00:00, confidence not recorded.
  - readme: https://github.com/khanhnamle1994/cracking-the-data-science-interview (fetched 2026-08-28T04:08:57.828125+00:00, sha 567a671f3fc2)
- Data as of 2026-08-30T08:39:29.467469+00:00.