This directory contains some sections that aren't part of the primary set of workshop labs, but illustrate some interesting and fun things.
- Introducing word2vec
- A less basic version of word2vec
- Using convolutional NNs for text classification, and TensorBoard
- Using convolutional NNs for text classification, part II: using learned word embeddings
If you would like to play around with them, they "should" still work, though they have not been tested with the current version of TensorFlow (version .11 as of this writing).
For some of these sections, we'll have you download some data files. For convenience, we list them here:
https://storage.googleapis.com/oscon-tf-workshop-materials/saved_word2vec_model.zip https://storage.googleapis.com/oscon-tf-workshop-materials/processed_reddit_data/reddit_post_title_words.zip https://storage.googleapis.com/oscon-tf-workshop-materials/processed_reddit_data/news_aww/reddit_data.zip https://storage.googleapis.com/oscon-tf-workshop-materials/learned_word_embeddings/reddit_embeds.zip
(Thanks to reddit, for allowing us to use some post data for a training corpus.)
If you're running the Docker image, and have mounted a data directory via something like the following (as in the installation instructions):
$ docker run -v `pwd`/workshop-data:/workshop-data -it \
-p 6006:6006 -p 8888:8888 gcr.io/google-samples/tf-workshop:v3then copy the downloads into that directory so that they're accessible both inside and outside the container.
Thanks to Denny Britz for this code: https://github.com/dennybritz/cnn-text-classification-tf, which we adapted for some of the workshop sections.
Thanks also to reddit, for allowing us to use some post data for a training corpus.