stanford-tensorflow-tutorials (chiphuyen/stanford-tensorflow-tutorials)
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What is this?
This is the code repository for Stanford's CS 20 course, 'TensorFlow for Deep Learning Research,' containing the example code used throughout the lectures.
Is this a reusable library or just course code?
It's a set of teaching examples tied to lecture content, not a library meant to be imported into other projects.
How do I get the examples running?
Clone the repo and follow the instructions in the setup folder, which lists everything needed to run the code.
What Python and TensorFlow version do I need?
The course materials were built with Python 3.6 and TensorFlow 1.4.1.
Will this still work with a modern TensorFlow install?
The repo is archived and pinned to TensorFlow 1.4.1, a pre-2.x release with a very different API, so running the examples on current TensorFlow likely requires adapting the code.
What topics does the course cover?
Based on the included materials and topics list, the course covers deep learning fundamentals, NLP, and a chatbot example built in TensorFlow.
Where can I find the full lecture notes?
The README points to an external course page with the detailed syllabus and lecture notes, since this repo only holds the code.
Is there an updated version for a later year?
No, the repo is archived; a separate '2017' folder and linked website hold the previous year's code and notes instead.
What are similar projects?
cs231n.github.io, nlp_course, Deep-Learning-Papers-Reading-Roadmap, pytorch-handbook, d2l-en, DeepLearning, stanford-cs-229-machine-learning, awesome-deep-learning-papers
Which topics is it in?
university, deep-neural-networks, students, python3, tensorflow, natural-language-processing, course, neural-network, academic-research, nlp, chatbot, deprecated