[DOC] Add to toc tree depth to enable multiple level menu (#1081) (#1108)

* Add toc tree depth to enable multiple level menu.

* Add index page for each chapter
To enable multiple level contents on the navigation bar

* Refactor sub-index pages into rst format

Author: WANG, Chen

docs/examples/index.rst

@@ -26,10 +26,9 @@ Word Embedding
 
 .. toctree::
    :hidden:
-   :maxdepth: 1
+   :maxdepth: 2
 
-   word_embedding/word_embedding.ipynb
-   word_embedding/word_embedding_training.ipynb
+   word_embedding/index
 
 
 Language Model
@@ -47,9 +46,9 @@ Language Model
 
 .. toctree::
    :hidden:
-   :maxdepth: 1
+   :maxdepth: 2
 
-   language_model/language_model.ipynb
+   language_model/index
 
 
 Machine Translation
@@ -72,10 +71,9 @@ Machine Translation
 
 .. toctree::
    :hidden:
-   :maxdepth: 1
+   :maxdepth: 2
 
-   machine_translation/gnmt.ipynb
-   machine_translation/transformer.ipynb
+   machine_translation/index
 
 
 Sentence Embedding
@@ -106,11 +104,9 @@ Sentence Embedding
 
 .. toctree::
    :hidden:
-   :maxdepth: 1
+   :maxdepth: 2
 
-   sentence_embedding/elmo_sentence_representation.ipynb
-   sentence_embedding/self_attentive_sentence_embedding.ipynb
-   sentence_embedding/bert.ipynb
+   sentence_embedding/index
 
 
 Sentiment Analysis
@@ -126,9 +122,9 @@ Sentiment Analysis
 
 .. toctree::
    :hidden:
-   :maxdepth: 1
+   :maxdepth: 2
 
-   sentiment_analysis/sentiment_analysis.ipynb
+   sentiment_analysis/index
 
 
 Sequence Sampling
@@ -145,6 +141,6 @@ Sequence Sampling
 
 .. toctree::
    :hidden:
-   :maxdepth: 1
+   :maxdepth: 2
 
-   sequence_sampling/sequence_sampling.ipynb
+   sequence_sampling/index

docs/examples/language_model/index.rst

@@ -0,0 +1,21 @@
+Language Model
+==============
+
+.. container:: cards
+
+   .. card::
+      :title: LSTM-based Language Models
+      :link: language_model.html
+
+      Learn what a language model is, what it can do, and how to train a word-level language model
+      with truncated back-propagation-through-time (BPTT).
+
+
+.. toctree::
+   :hidden:
+   :maxdepth: 2
+
+   language_model.ipynb
+
+
+

docs/examples/machine_translation/index.rst

@@ -0,0 +1,28 @@
+Machine Translation
+===================
+
+.. container:: cards
+
+   .. card::
+      :title: Google Neural Machine Translation
+      :link: gnmt.html
+
+      Learn how to train Google Neural Machine Translation, a seq2seq with attention model.
+
+   .. card::
+      :title: Machine Translation with Transformer
+      :link: transformer.html
+
+      Learn how to use a pre-trained transformer translation model for English-German translation.
+
+
+
+.. toctree::
+   :hidden:
+   :maxdepth: 2
+
+   gnmt.ipynb
+   transformer.ipynb
+
+
+

docs/examples/sentence_embedding/index.rst

@@ -0,0 +1,36 @@
+Sentence Embedding
+==================
+
+.. container:: cards
+
+   .. card::
+      :title: ELMo: Deep Contextualized Word Representations
+      :link: elmo_sentence_representation.html
+
+      See how to use GluonNLP's model API to automatically download the pre-trained ELMo
+      model from NAACL2018 best paper, and extract features with it.
+
+   .. card::
+      :title: A Structured Self-attentive Sentence Embedding
+      :link: self_attentive_sentence_embedding.html
+
+      See how to use GluonNLP to build more advanced model structure for extracting sentence
+      embeddings to predict Yelp review rating.
+
+   .. card::
+      :title: BERT: Bidirectional Encoder Representations from Transformers
+      :link: bert.html
+
+      See how to use GluonNLP to fine-tune a sentence pair classification model with
+      pre-trained BERT parameters.
+
+.. toctree::
+   :hidden:
+   :maxdepth: 2
+
+   elmo_sentence_representation.ipynb
+   self_attentive_sentence_embedding.ipynb
+   bert.ipynb
+
+
+

docs/examples/sentiment_analysis/index.rst

@@ -0,0 +1,19 @@
+Sentiment Analysis
+==================
+
+.. container:: cards
+
+   .. card::
+      :title: Sentiment Analysis by Fine-tuning Word Language Model
+      :link: sentiment_analysis.html
+
+      See how to fine-tune a pre-trained language model to perform sentiment analysis on movie reviews.
+
+
+.. toctree::
+   :hidden:
+   :maxdepth: 2
+
+   sentiment_analysis.ipynb
+
+

docs/examples/sequence_sampling/index.rst

@@ -0,0 +1,21 @@
+Sequence Sampling
+=================
+
+.. container:: cards
+
+   .. card::
+      :title: Sequence Generation with Sampling and Beam Search
+      :link: sequence_sampling.html
+
+      Learn how to generate sentence from pre-trained language model through sampling and beam
+      search.
+
+
+.. toctree::
+   :hidden:
+   :maxdepth: 2
+
+   sequence_sampling.ipynb
+
+
+

docs/examples/word_embedding/index.rst

@@ -0,0 +1,29 @@
+Word Embedding
+==============
+
+.. container:: cards
+
+   .. card::
+      :title: Pre-trained Word Embeddings
+      :link: word_embedding.html
+
+      Basics on how to use word embedding with vocab in GluonNLP and apply it on word similarity and
+      analogy problems.
+
+   .. card::
+      :title: Word Embeddings Training and Evaluation
+      :link: word_embedding_training.html
+
+      Learn how to train fastText and word2vec embeddings on your own dataset, and determine
+      embedding quality through intrinsic evaluation.
+
+
+.. toctree::
+   :hidden:
+   :maxdepth: 2
+
+   word_embedding.ipynb
+   word_embedding_training.ipynb
+
+
+