Fix errors in SETUP.md

.gitignore

@@ -1,3 +1,5 @@
+assets/images/
+**/data/*
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

README.md

@@ -1,41 +1,48 @@
 # Natural Language Processing with PyTorch
+
 _Build Intelligent Language Applications Using Deep Learning_
-<br>By Delip Rao and Brian McMahan
+By Delip Rao and Brian McMahan
+
+Welcome. This repository is a fork of the [original repository](https://github.com/delip/PyTorchNLPBook) for the book _Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning_. (2019). ISBN: 9781491978221. Available on [Amazon](https://www.amazon.com/Natural-Language-Processing-PyTorch-Applications/dp/1491978236/) and [O'Reilly Media](https://learning.oreilly.com/library/view/natural-language-processing/9781491978221).
 
+This fork addresses the following issues with the original repository.
 
-Welcome. This is a companion repository for the book [Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning](https://www.amazon.com/Natural-Language-Processing-PyTorch-Applications/dp/1491978236/).
+| Issue | Description | Resolution |
+|-------|-------------|------------|
+|       |             |            |
 
+## Table of Contents
 
-Table of Contents
-=================
+---
 
 <!--ts-->
 * Get Started!
-* [Chapter 1: Introduction](https://github.com/joosthub/PyTorchNLPBook/tree/master/chapters/chapter_1)
+* [Chapter 1: Introduction](https://github.com/ciioprof0/PyTorchNLPBook/tree/master/chapters/chapter_1)
   * PyTorch Basics
-* Chapter 2: A Quick Tour of NLP
-* [Chapter 3: Foundational Components of Neural Networks](https://github.com/joosthub/PyTorchNLPBook/tree/master/chapters/chapter_3)
+* Chapter 2: [A Quick Tour of NLP](https://github.com/ciioprof0/PyTorchNLPBook/tree/master/chapters/chapter_1)
+  * In-text examples
+* [Chapter 3: Foundational Components of Neural Networks](https://github.com/ciioprof0/PyTorchNLPBook/tree/master/chapters/chapter_3)
   * In-text examples
   * Diving deep into supervised training
   * Classifying sentiment of restaurant reviews using a Perceptron
-* [Chapter 4: Feed-forward Networks for NLP](https://github.com/joosthub/PyTorchNLPBook/tree/master/chapters/chapter_4)
+* [Chapter 4: Feed-forward Networks for NLP](https://github.com/ciioprof0/PyTorchNLPBook/tree/master/chapters/chapter_4)
   * Limitations of the Perceptron
   * Introducing Multi-layer Perceptrons (MLPs)
   * Introducing Convolutional Neural Networks (CNNs)
   * Surname Classification with an MLP
   * Surname Classification with a CNN
-* [Chapter 5: Embedding Words and Types](https://github.com/joosthub/PyTorchNLPBook/tree/master/chapters/chapter_5)
+* [Chapter 5: Embedding Words and Types](https://github.com/ciioprof0/PyTorchNLPBook/tree/master/chapters/chapter_5)
   * Using Pretrained Embeddings
-  * Learning Continous Bag-of-words Embeddings (CBOW)
+  * Learning Continuous Bag-of-words Embeddings (CBOW)
   * Transfer Learning using Pre-trained Embeddings
-* [Chapter 6: Sequence Modeling for NLP](https://github.com/joosthub/PyTorchNLPBook/tree/master/chapters/chapter_6)
+* [Chapter 6: Sequence Modeling for NLP](https://github.com/ciioprof0/PyTorchNLPBook/tree/master/chapters/chapter_6)
   * A sequence representation for Surnames
-* [Chapter 7: Intermediate Sequence Modeling for NLP](https://github.com/joosthub/PyTorchNLPBook/tree/master/chapters/chapter_7)
+* [Chapter 7: Intermediate Sequence Modeling for NLP](https://github.com/ciioprof0/PyTorchNLPBook/tree/master/chapters/chapter_7)
   * Generating novel surnames from sequence representations
-  * Uncondition generation
+  * Unconditioned generation
   * Conditioned generation
-* [Chapter 8: Advanced Sequence Modeling for NLP](https://github.com/joosthub/PyTorchNLPBook/tree/master/chapters/chapter_8)
-  * Understanding PackedSequences 
+* [Chapter 8: Advanced Sequence Modeling for NLP](https://github.com/ciioprof0/PyTorchNLPBook/tree/master/chapters/chapter_8)
+  * Understanding PackedSequences
   * Sequence to Sequence Learning
   * Attention
   * Neural Machine Translation

SETUP.md

@@ -1,71 +1,57 @@
 # Setup Instructions
 
-The recommended setup is described below. Modifications to this setup will be called out as appropriate. 
+The recommended setup is described below. Modifications to this setup will be called out as appropriate.
 
+## Clone the Repository
 
-## Conda Environment
+Clone the [repository](https://github.com/ciioprof0/PyTorchNLPBook) from GitHub using one of the options below:
 
-It is highly recommended that a conda environment is used to house your PyTorch installation.  This has the benefit of insulating against vesion differences.  Alternatives to using conda for installation can be found on [pytorch.org](https://pytorch.org). 
+- Option A. The web URL:
 
-### Create the environment
-
-```
-# Create the environment
-conda create --name nlpbook
-source activate nlpbook
+```{bash}
+git clone https://github.com/ciioprof0/PyTorchNLPBook.git
 ```
 
-### Install PyTorch
+- Option B. The SSH URL:
 
-Note, this installs the GPU versions as of January, 2019.  If this command changes in the future, this README will be updated accordingly. If it is not, please file an issue. 
-
-```
-conda install pytorch torchvision -c pytorch
+```{bash}
+git clone [email protected]:ciioprof0/PyTorchNLPBook.git
 ```
 
-If you need the CPU versions, want to use pip install of conda, or a host of other configuration variations, please consult the website.  They have done a great job of making it easy to retrieve the correct install command. 
-
-### Download the Repositroy
-
-You can download the repository from [this URL](https://nlproc.info/PyTorchNLPBook/repo/) using git or downloading the repository as a zip file. As of January, 2019, this URL redirects to https://github.com/joosthub/PyTorchNLPBook and you can use the following commands to clone the repository:
+- Option C. The GitHub CLI:
 
-```
-git clone [email protected]:joosthub/PyTorchNLPBook.git
+```{bash}
+gh repo clone ciioprof0/PyTorchNLPBook
 ```
 
-Or
+## Create the local environment
 
-```
-git clone https://github.com/joosthub/PyTorchNLPBook.git
-```
+Install the Conda Environment
 
-### Install the remaining packages with the requirements file
+It is highly recommended that a conda environment is used to house your PyTorch installation. This has the benefit of insulating against version differences. See [Installing conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html) for instructions on how to install conda pn your system. The [Miniconda](https://docs.anaconda.com/miniconda/) installer is sufficient for this purpose.
 
-Inside the repository is a requirements file which can be used to install the remaining packages. 
+Alternatives to using conda for installation can be found on [pytorch.org](https://pytorch.org).
 
-```
-cd PyTorchNLPBook
-pip install -r requirements.txt
-```
+### Create the conda environment
 
-### Installing the jupyter kernel
+When you have conda installed, you can create an environment with the following command from the project root directory:
 
-```
-python -m ipykernel install --user --name nlpbook
+Step 1. Create the environment from the `environment.yml` file:
+
+```{bash}
+conda env create -f setup/conda/environment.yml --no-default-packages
 ```
 
-### Download the data
+Step 2. Activate the environment:
 
-```
-cd data
-./get-all-data.sh
+```{bash}
+source activate nlpbook
 ```
 
-Note: GloVe is not bundled in our data downloader.  See `data/README.md` for more information.
+Step 3. Download the data:
 
-### Run the notebook server
+_Note_. The script below has not yet been updated to download the missing data files. Please see the `data/README.md` for manual installation instructions.
 
-```
-# run from the top level. if running commands in order, will need to `cd ..`
-jupyter notebook
-```
+```{bash}
+bash src/get-all-data.sh
+```