# snowkylin/tensorflow-handbook

简单粗暴 TensorFlow 2 | A Concise Handbook of TensorFlow 2 | 一本简明的 TensorFlow 2 入门指导教程

Repository: https://github.com/snowkylin/tensorflow-handbook
Canonical: https://ross.abutalabs.com/products/tensorflow-handbook
Homepage: https://tf.wiki
Language: Jupyter Notebook
License Family: other
Last push: 2023-03-21T05:24:15+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": 2800, "days_push": 1261, "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 3925, forks 817 (observed 2026-08-28T04:08:29.848183+00:00)

## What it is
A concise open-source handbook (available online at tf.wiki in Simplified Chinese, Traditional Chinese, and English) for getting started with TensorFlow 2, based on Keras and Eager Execution. It includes example Jupyter Notebook code covering model building, training, deployment, and TensorFlow modules like tf.data and TensorBoard.

## Use cases
- learn tensorflow 2 from scratch
- tensorflow 2 tutorial with keras
- understand eager execution in tensorflow
- find example code for cnn and rnn in tensorflow
- learn to deploy tensorflow models with tf serving
- tensorflow study guide in chinese
- gpu setup guide for tensorflow

## When to choose
- you have basic Python and machine learning knowledge and want a quick, practical introduction to TensorFlow 2
- you prefer a free bilingual (Chinese/English) online book with runnable example code
- you want coverage of both model training and deployment topics like TensorFlow Serving

## When to avoid
- you need up-to-date coverage of the latest TensorFlow versions, as the content targets TensorFlow 2.0-2.2
- you want a formal textbook with a license file and active maintenance guarantees
- you are learning PyTorch or another framework

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, documentation
- domain: deep-learning, machine-learning, tutorials, education
- platform: python, cross-platform
- tags: tensorflow, keras, eager-execution, handbook, jupyter-notebook, chinese, bilingual

## Member repositories
- snowkylin/tensorflow-handbook (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:29.848183+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 2026-08-29T18:24:44.455567+00:00, confidence not recorded.
  - readme: https://github.com/snowkylin/tensorflow-handbook (fetched 2026-08-28T04:08:29.848183+00:00, sha b40ae91aa72a)
  - homepage: https://tf.wiki (fetched 2026-08-29T09:18:47.008705+00:00, sha ff083e25bb00)
  - site_page: https://tf.wiki/zh_hans/basic/installation.html (fetched 2026-08-29T09:18:47.012527+00:00, sha e723b4cfbb97)
  - site_page: https://tf.wiki/zh_hant/basic/installation.html (fetched 2026-08-29T09:18:47.015049+00:00, sha 11f73db1dd7c)
  - site_page: https://tf.wiki/en/basic/installation.html (fetched 2026-08-29T09:18:47.017091+00:00, sha 49d24358e73f)
  - site_page: https://tf.wiki/en/deployment/serving.html (fetched 2026-08-29T09:18:47.019286+00:00, sha edfcafa41f50)
- Data as of 2026-08-30T08:39:29.467469+00:00.