stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Code examples from Stanford's CS 20 TensorFlow for Deep Learning Research course, covering deep learning, NLP, and chatbot construction in Python and TensorFlow 1.4.
This repository holds the code examples that accompanied Stanford's CS 20 course, titled TensorFlow for Deep Learning Research. TensorFlow is a software library for building and training machine learning models, and the course was designed to teach researchers and students how to use it for deep learning projects.
The examples are written in Python 3.6 and target TensorFlow version 1.4.1. The topics covered across the course materials include general deep learning techniques, natural language processing, and chatbot construction, based on the listed subject tags. Setup instructions and a list of required dependencies are included in the repository's setup folder.
The repository also retains materials from an earlier 2017 version of the course, stored in a separate folder. Full lecture notes and the course syllabus were hosted at cs20.stanford.edu.
The README is sparse and does not describe individual examples or explain what each file does. This appears to be primarily a companion resource for enrolled students following the course, rather than a standalone tutorial series designed to be read on its own. The code is released under the MIT license.
Where it fits
- Follow Stanford CS 20 deep learning examples locally to learn TensorFlow 1.4 techniques.
- Study NLP and chatbot construction code from the course to practice deep learning patterns.
- Reference the 2017 course materials alongside updated examples to see how TensorFlow evolved.