# GoogleCloudPlatform/data-science-on-gcp

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017

Repository: https://github.com/GoogleCloudPlatform/data-science-on-gcp
Canonical: https://ross.abutalabs.com/products/data-science-on-gcp
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: data-analysis, data-visualization, cloud-computing, machine-learning, data-pipeline, data-processing, data-science, data-engineering
Last push: 2026-02-20T21:04:56+00:00

## Health v2 (maintenance only)
Score: 63/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 68, release rhythm 35, longevity 100
- inputs: {"age_days": 3491, "days_push": 194, "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 1427, forks 727 (observed 2026-08-28T04:04:41.942086+00:00)

## What it is
Companion source code repository for the O'Reilly book 'Data Science on the Google Cloud Platform' by Valliappa Lakshmanan, provided as Jupyter Notebooks. It demonstrates end-to-end data science workflows on GCP, including data pipelines, BigQuery, and machine learning with TensorFlow.

## Use cases
- learn data science on google cloud platform
- build data pipelines with bigquery and cloud dataflow
- train machine learning models on gcp
- follow along with the data science on gcp book exercises
- learn bigquery ml and tensorflow on cloud
- practice gcp data engineering workflows

## When to choose
- you are reading the book and want its working code
- you want hands-on GCP data science and ML tutorials
- you need example pipelines using BigQuery, Dataflow, and Vertex AI

## When to avoid
- you need production-ready data science tooling rather than educational examples
- you use a cloud provider other than Google Cloud
- you want a maintained library with an API rather than notebook code

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, etl, data-science, data-visualization
- domain: data-science, cloud-computing, machine-learning
- platform: python, cloud, jvm
- tags: google-cloud-platform, jupyter-notebooks, bigquery, book-companion-code, oreilly, data-pipeline, tensorflow, data-engineering

## Member repositories
- GoogleCloudPlatform/data-science-on-gcp (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:41.942086+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 2026-08-30T04:37:20.998350+00:00, confidence not recorded.
  - readme: https://github.com/GoogleCloudPlatform/data-science-on-gcp (fetched 2026-08-28T04:04:41.942086+00:00, sha 28c2c96a21a1)
- Data as of 2026-08-30T08:39:29.467469+00:00.