# vahidk/EffectiveTensorflow

TensorFlow tutorials and best practices.

Repository: https://github.com/vahidk/EffectiveTensorflow
Canonical: https://ross.abutalabs.com/products/effectivetensorflow
Homepage: https://twitter.com/VahidK
License Family: other
Topics: tensorflow, neural-network, deep-learning, machine-learning, ebook
Last push: 2020-10-22T05:26:17+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": 3319, "days_push": 2141, "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 8585, forks 876 (observed 2026-08-28T04:10:23.665051+00:00)

## What it is
Effective TensorFlow 2 is an ebook-style series of tutorials and best practices for TensorFlow 2.x, covering fundamentals like tensors, broadcasting, control flow, and numerical stability. It is an updated version of the popular TensorFlow 1.x guide, with a v1 branch retained for legacy content.

## Use cases
- learn tensorflow 2 basics
- understand broadcasting in tensorflow
- tensorflow best practices guide
- migrate from tensorflow 1 to tensorflow 2
- learn numerical stability in tensorflow
- deep learning tutorial ebook

## When to choose
- you are learning TensorFlow 2.x and want concise, example-driven explanations
- you know NumPy and want to map that knowledge to TensorFlow
- you want a free ebook-style reference on TensorFlow fundamentals

## When to avoid
- you need official, exhaustive API documentation
- you need tutorials for PyTorch or other frameworks
- you need actively updated content for the latest TensorFlow releases

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: deep-learning, machine-learning, tutorials
- platform: python
- tags: tensorflow, ebook, tutorials, best-practices, neural-networks

## Member repositories
- vahidk/EffectiveTensorflow (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:23.665051+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 2026-08-29T17:26:15.436139+00:00, confidence not recorded.
  - readme: https://github.com/vahidk/EffectiveTensorflow (fetched 2026-08-28T04:10:23.665051+00:00, sha 42d2da17fac1)
- Data as of 2026-08-30T08:39:29.467469+00:00.