LSTM on books data

hatt_train.ipynb

@@ -2,7 +2,10 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The code in this notebook is based on [Richard Liao's implementation of hierarchical attention networks](https://github.com/richliao/textClassifier/blob/master/textClassifierHATT.py) and a related [Google group discussion](https://groups.google.com/forum/#!topic/keras-users/IWK9opMFavQ). The notebook also includes code from [Keras documentation](https://keras.io/) and [blog](https://blog.keras.io/using-pre-trained-word-embeddings-in-a-keras-model.html) as well as this [word2vec tutorial](http://adventuresinmachinelearning.com/gensim-word2vec-tutorial/)."
    ]
@@ -171,11 +174,11 @@
     "texts = []\n",
     "\n",
     "for idx in range(train_data.shape[0]):\n",
-    "    text = train_data['text'][idx]\n",
+    "    text = train_data['text'].iloc[idx]\n",
     "    texts.append(text)\n",
     "    sentences = nltk.tokenize.sent_tokenize(text)\n",
     "    reviews.append(sentences)\n",
-    "    labels.append(train_data['rating'][idx])"
+    "    labels.append(train_data['rating'].iloc[idx])"
    ]
   },
   {