# nfmcclure/tensorflow_cookbook

Code for Tensorflow Machine Learning Cookbook

Repository: https://github.com/nfmcclure/tensorflow_cookbook
Canonical: https://ross.abutalabs.com/products/tensorflow_cookbook
Homepage: https://www.packtpub.com/big-data-and-business-intelligence/tensorflow-machine-learning-cookbook-second-edition
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: tensorflow, tensorflow-cookbook, linear-regression, neural-network, tensorflow-algorithms, rnn, cnn, svm, nlp, packtpub, machine-learning, tensorboard, classification, regression, kmeans-clustering, genetic-algorithm, ode
Last push: 2024-05-23T20:56:53+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3736, "days_push": 832, "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 6238, forks 2365 (observed 2026-08-28T04:09:40.838112+00:00)

## What it is
The official code repository for the book 'TensorFlow Machine Learning Cookbook' by Nick McClure, containing Jupyter Notebook recipes for TensorFlow algorithms. It covers topics from basic tensors through regression, SVMs, neural networks, CNNs, RNNs, and NLP.

## Use cases
- learn tensorflow through worked examples
- find code recipes for implementing neural networks in tensorflow
- study cnn and rnn implementations
- learn linear regression and svm in tensorflow
- tensorflow cookbook companion code
- practice machine learning with jupyter notebooks

## When to choose
- you are reading or studying the TensorFlow Machine Learning Cookbook
- you want notebook-style examples of classic ML algorithms in TensorFlow
- you are learning TensorFlow fundamentals like graphs, variables, and placeholders

## When to avoid
- you need production-ready or maintained TensorFlow code
- you want modern TensorFlow 2.x / Keras idioms
- you need a library rather than educational example code

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, nlp, data-science
- domain: machine-learning, deep-learning, tutorials
- platform: python
- tags: tensorflow, jupyter-notebooks, cookbook, neural-networks, cnn, rnn, svm, linear-regression, tensorboard, packt-book, natural-language-processing

## Member repositories
- nfmcclure/tensorflow_cookbook (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:40.838112+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 2026-08-29T17:47:11.668009+00:00, confidence not recorded.
  - readme: https://github.com/nfmcclure/tensorflow_cookbook (fetched 2026-08-28T04:09:40.838112+00:00, sha de94cf9288c6)
- Data as of 2026-08-30T08:39:29.467469+00:00.