├── Concrete_NLP_advice_SLIDES_ODSC_1103.pdf ├── NLP_notebook.ipynb ├── README.md ├── requirements.txt ├── seed_text.txt └── socialmedia_relevant_cols.csv /Concrete_NLP_advice_SLIDES_ODSC_1103.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/hundredblocks/concrete_NLP_tutorial/f1eab4fb0cf054687258ab2bca01c6d5806a22f9/Concrete_NLP_advice_SLIDES_ODSC_1103.pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # NLP Workshop for ODSC 2017 2 | Feel free to follow along in this notebook, or download it and run it yourself. Instructions below. 3 | 4 | # Installation instructions 5 | 6 | #### clone the repository 7 | 8 | #### download pretrained google word vectors 9 | 10 | Run `python -m gensim.downloader --download word2vec-google-news-300` or follow the instructions in the gensim documentation. 11 | 12 | #### download pretrained char-rnn for Yelp 13 | `curl -O https://s3.amazonaws.com/yelp-weights-files/Sep-26-all-00-0.7280.hdf5` 14 | 15 | rename the file to 'pretrained-yelp.hdf5' 16 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | keras 2 | tensorflow 3 | nltk 4 | pandas 5 | numpy 6 | matplotlib 7 | umap-learn 8 | gensim 9 | lime 10 | -------------------------------------------------------------------------------- /seed_text.txt: -------------------------------------------------------------------------------- 1 | 'This is a text file. This file is just something to help the model get started! You can use anything.' 2 | -------------------------------------------------------------------------------- /socialmedia_relevant_cols.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/hundredblocks/concrete_NLP_tutorial/f1eab4fb0cf054687258ab2bca01c6d5806a22f9/socialmedia_relevant_cols.csv --------------------------------------------------------------------------------