# PacktPublishing/The-Kaggle-Book

Code Repository for The Kaggle Book, Published by Packt Publishing

Repository: https://github.com/PacktPublishing/The-Kaggle-Book
Canonical: https://ross.abutalabs.com/products/the-kaggle-book
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2026-03-02T14:23:19+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 70, release rhythm 35, longevity 100
- inputs: {"age_days": 1813, "days_push": 184, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2333, forks 469 (observed 2026-08-28T04:06:37.917122+00:00)

## What it is
The official code repository for 'The Kaggle Book' by Packt Publishing, containing Jupyter Notebook examples from two Kaggle Grandmasters. It covers competitive data science techniques including ensembling, feature engineering, adversarial validation, AutoML, and transfer learning.

## Use cases
- learn how to compete in Kaggle competitions
- study feature engineering examples for tabular data
- understand ensembling and model stacking techniques
- practice machine learning on vision and NLP competition problems
- learn hyperparameter tuning and AutoML workflows
- find example notebooks for adversarial validation

## When to choose
- you are reading The Kaggle Book and want its companion code
- you want worked Jupyter Notebook examples of Kaggle competition techniques
- you are a beginner-to-intermediate data scientist learning competitive ML

## When to avoid
- you need a production-ready ML library or framework
- you want maintained software tooling rather than educational notebooks
- you are not interested in Kaggle-style competitions or book-based learning

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, data-science, benchmarking
- domain: data-science, machine-learning, tutorials
- platform: python
- tags: kaggle, competitions, jupyter-notebooks, book-code, feature-engineering, ensembling

## Member repositories
- PacktPublishing/The-Kaggle-Book (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:37.917122+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 2026-08-30T02:37:54.816949+00:00, confidence not recorded.
  - readme: https://github.com/PacktPublishing/The-Kaggle-Book (fetched 2026-08-28T04:06:37.917122+00:00, sha f859c8332435)
- Data as of 2026-08-30T08:39:29.467469+00:00.