DH_PythonLibraries_JupyterNotebooks

bitly link to this notebook: http://bit.ly/2yGHuot

link to slides

Files and resources for using Data Science, Python, and Jupyter Notebooks in the practice of Digital Humanities

To use the notebooks in a browser go to

Derek's e-mail: [email protected]

Agenda

1. Intro

• Ice breaking
• Expectations
• "Level Setting"

2. The basics

• Jupyter Notebooks
• Python
• NLP/NLTK

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3. The NLTK Book

• Chapter 1 (book module)
• Chapter 2 (corpora module)
• Chapter 3 (raw text)

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4. Machine Learning and Text

• Simple Webscraping to get a corpus
• Machine Learning intro
• Look at a Machine Learning Problem
• Apply Machine Learning to text

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5. Dive in and Questions

Notebooks on github

• Intro to Jupyter Notebook

• Brief_Overview_of_Python

• NLTK Overview

• NLTK Book, Chapter 1 Exercises

• NLTK Book, Chapter 2 Exercises

• NLTK Book, Chapter 3 Exercises

• Webscraping to get a corpus

• Machine Learning Overview

• Machine Learning Example with Regression

• Text Classification (Unsupervised Learning)

Resources

• Markdown Cheetsheet
• Get Python
• Download Anaconds to get Jupyter Notebook
• PyCharm Python Integrated Development Environment
• CoLab Google's online iPython notebook
• Python Software Foundation Everything Python
• World Wide Web Consortium (W3C) Python Tutorial
• Python Data Science Handbook
• NLTK Documentation
• Natural Language Processing with Python (The NLTK book)

Jupyter Notebooks

• Download Anaconds to get Jupyter Notebook
• Intro to Jupyter Notebook file on github

Python

Get Python

Highlights

• High Level programming language.
• General purpose
• Named after Monty Python
• Written in English and relatively easy to read
• Widely supported by a strong user community
• Around since 1990

Dive in

• Brief Overview of Python file on github
• Brief Overview of Python on Colab note: you will need to copy this to your own google account in order to run the notebook
• Python Software Foundation Everything Python
• World Wide Web Consortium (W3C) Python Tutorial
• PyCharm Python Integrated Development Environment

Python Libraries

• NLTK
  • NLTK Documentation
    
  • Natural Language Processing with Python (The NLTK book)
    
  • NLTK Overview notebook
    
  • NLTK Book, Chapter 1 Exercises
• Pandas
  • Pandas: Python Data Analysis Library
• Numpy
• Scikit Learn
• Beutiful Soup
• urllib
• Wordcloud
• Mathplotlib
• Gensim (Word2Vec)
• Tensorflow

Machine Learning and NLP

• Python Data Science Handbook