#!/usr/bin/env python
# coding: utf-8

# # Useful Resources
# 

# ### Programming Basics 
# * [Codecademy](https://www.codecademy.com/learn/learn-python) - Online learning platform which offers free interactive lessons covering the very basics of programming languages.
# * [Google's Python Class](https://developers.google.com/edu/python/) - A combination of written materials, instructional videos and coding exersises to practice Python programming. 
# * [Pyschools](http://www.pyschools.com/) - Practical python tutorials for beginners and beyond. Note - you must have a google account to sign-up.
# * [Udacity](https://www.udacity.com/course/programming-foundations-with-python--ud036) - Introduction python programming class with mini-projects in each lesson.
# * [Tutorialspoint](https://www.tutorialspoint.com/python/python_basic_syntax.htm) - Basics of python syntax.
# ---

# ### Software & Libraries
# * [Anaconda](https://www.anaconda.com/download/#macos) - Suite of data science applications 
# * [Gensim](https://radimrehurek.com/gensim/) - Topic Modelling toolkit for Python
# * [NLTK](http://www.nltk.org/) - Natural Language Toolkit
# 
# ---
# 

# ### Python Resources
# * [The Python Wiki](https://wiki.python.org/moin/FrontPage) - A comprehensive encyclopedia of python related information including a beginners guide, common problems and links to many useful resources.
# * [Stack Overflow](https://stackoverflow.com/) - An excellent community driven question-answer problem solving resource for even the trickiest of python conundrums.
# 
# ---

# ### Further Explorations
# * [Voyant](https://voyant-tools.org/) - Open source web application for text analysis featuring a plethora of data and visualization tools.
# * [Big Data by Neal Caren](http://nealcaren.web.unc.edu/big-data/) - Tutorials which cover the fundamentals of quantitative text analysis for social scientists.
# ---

# ### Open Source Materials
# 
# * [Project Gutenberg](http://gutenberg.ca/index.html) - Digital editions of classic literature in the public domain
# 
# ---

# [CC BY-SA](https://creativecommons.org/licenses/by-sa/4.0/) From [The Art of Literary Text Analysis](ArtOfLiteraryTextAnalysis.ipynb) by [Stéfan Sinclair](http://stefansinclair.name) &amp; [Geoffrey Rockwell](http://geoffreyrockwell.com). Edited and revised by [Melissa Mony](http://melissamony.com). <br /> 

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