The Berkeley Digital Humanities Working Group began in 2011 as a place to facilitate interdisciplinary conversations around topics in the Digital Humanities (broadly defined).  We welcome participants from all disciplinary backgrounds, beginners and experts in digital skills, students, faculty, and staff.  The agenda for our biweekly meetings is participant driven, and we typically hold a variety of meetings, including project presentations, hackerspace-style open project days, and mashup meetings with other working groups.  Our major project for the year is planning the DH Faire

LaTeX is a widely used document creation software which can help you improve the presentation of homework, papers, academic articles and even presentations. It produces perfectly formatted equations, allows for the easy integration of multiple files, and can make creating bibliographies easy. In this workshop, we'll teach you how to get started in TeX, and provide you with templates and code that you can use going forward. Specifically, this workshop will cover:

For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter (formerly IPython) notebook. The following plot types will be covered:

• line
• bar
• scatter
• boxplot

We'll also learn about styles and customizing plots.

Throughout the workshop, we'll discuss the plot types best suited for particular kinds of data.

In this workshop we will cover the most common CTA task: supervised classification. Using the Python library scikit-learn, we will implement Logistic Regression and Random Forest methods to perform sentiment analysis. Optional: introduction to word vector representations with Word2Vec.

Prior knowledge: Basic familiarity with Python is required if you wish to follow along with the tutorial. Completion of D-Lab's Python FUN!damentals workshop series will be sufficient.