OpenViSTAI · Agents · Blockchain · Crypto
Menu
AI Developer Tools & SDKs

TensorFlow Machine Learning Cookbook

A public GitHub collection of Jupyter Notebook code examples accompanying Nick McClure’s TensorFlow Machine Learning Cookbook, covering TensorFlow fundamentals and implementations of machine-learning methods.

Independent OpenViST project profile, based on linked sources.

TensorFlow Machine Learning Cookbook — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it as a chapter-organized code companion when learning TensorFlow or looking for notebook examples on a particular machine-learning method.

Who it is for

  • Learners studying TensorFlow concepts and machine-learning implementations.
  • Educators preparing notebook-based demonstrations of methods such as regression, clustering and neural networks.
  • Developers seeking example code to examine or adapt for TensorFlow learning projects.

Documented uses

  • Study TensorFlow basics including tensors, variables, operations and computational graphs.
  • Explore examples organized around regression, support vector machines, nearest-neighbor methods, neural networks and NLP.
  • Review material on convolutional and recurrent neural networks, model evaluation and taking TensorFlow to production.
Before you choose

Requirements & limits

The repository is public and identified as MIT-licensed.

  • The primary language is Jupyter Notebook, so the material is presented as notebooks rather than a single hosted application.
  • The chapter outline includes data-source guidance; check the relevant materials for data needed by a particular example.
  • Topics range from TensorFlow fundamentals through NLP, convolutional and recurrent networks, and production-related material.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Use the cookbook to find TensorFlow learning examples

Navigate the cookbook’s chapter index to choose a notebook topic for study.

Before you start

  • Access to the cookbook repository README.

Steps

  1. Open the repository README.

  2. Choose a chapter from its table of contents, such as linear regression, neural networks, or natural language processing.

  3. Follow the chapter’s listed topic links to explore the corresponding examples.

Expected outcome

A selected chapter and its linked cookbook topics for further learning.

Guide limitations

  • The README index alone does not specify environment setup or the steps to execute notebook examples.
Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
14 October 2026
Original website title
nfmcclure/tensorflow_cookbook · Official homepage title · retained in its source language