Detexify LaTeX handwritten symbol recognition Want a Mac app? Lucky you. The Mac app is finally stable enough. See how it works on Vimeo. Creating a great data science resume I hear a familiar story from a lot of aspiring data scientists: “I have sent out my resume to 25 companies, and I haven’t heard back from any of them! I have pretty good skills, and I think I have a pretty good resume. I don’t know what’s going on!” <code>classicthesis</code> - Waterfox This section is devoted to a template bundle which I developed for the typesetting system LaTeX. The first version of the template was released in early 2006. From the feedback and postcards I received so far, it seems to be in heavy use all over the world!
Exporting R tables in LaTeX Recently I have started using LaTeX for all my documents and presentations. Don’t ask me why, I just like how texts look there rather than in products of Microsoft (and I in general dislike MS… we have a long unpleasant history). So, I sometimes need to export tables from R into LaTeX. These tables can be huge, so exporting them manually is not an option.
Natbib reference sheet Reference sheet for natbib usage(Describing version 7.0b from 2002/02/27) For a more detailed description of the natbib package, LATEX the source file natbib.dtx. Overview The natbib package is a reimplementation of the LATEX \cite command, to work with both author-year and numerical citations. How to Produce Professional Documents with LaTeX – Michael Elliot King A simple guide to learning LaTeX for formatting your professional documents If you’ve seen a university level math or science assignment, or read something published in an academic journal, then you’ve seen the results of LaTeX and would recognize its fonts and formatting. What is LaTeX (pronounced lay-tek, NOT lay-teks) is a free, digital typesetting system used by professionals to produce beautiful, high-quality, publishable documents, typically in .pdf format. Rather than typing your document into a word processor, like Microsoft Word, your content is written in plain text in a text editor along with code to provide instructions.
Writing An Hadoop MapReduce Program In Python In this tutorial I will describe how to write a simple MapReduce program for Hadoop in the Python programming language. Even though the Hadoop framework is written in Java, programs for Hadoop need not to be coded in Java but can also be developed in other languages like Python or C++ (the latter since version 0.14.1). However, Hadoop’s documentation and the most prominent Python example on the Hadoop website could make you think that you must translate your Python code using Jython into a Java jar file. Obviously, this is not very convenient and can even be problematic if you depend on Python features not provided by Jython. Another issue of the Jython approach is the overhead of writing your Python program in such a way that it can interact with Hadoop – just have a look at the example in $HADOOP_HOME/src/examples/python/WordCount.py and you see what I mean. Our program will mimick the WordCount, i.e. it reads text files and counts how often words occur.
Git version control with Eclipse (EGit) - Tutorial - Waterfox Git version control with Eclipse (EGit) - Tutorial Copyright © 2009-2016 vogella GmbH Git with Eclipse (EGit) Sweave: Transition from Sweave to knitr Before knitr 1.0, it was compatible with Sweave for easier transition from Sweave to knitr, but the compatibility was dropped since v1.0 for (much) easier maintenance of this package. If you have an Rnw document written for Sweave, the first step you can do is to call Sweave2knitr() on it, and knitr will automatically correct the syntax (mainly chunk options, e.g. results=hide should be results='hide', and eval=true should be eval=TRUE, etc). library(knitr)Sweave2knitr('old-document.Rnw') # you will get old-document-knitr.Rnw by default # see ?Sweave2knitr for details Side-by-side content in beamer presentations « LaTeX Matters There are two ways (and possibly more) to place content side-by-side in a beamer presentation, the columns and the minipage environments. The first is a beamer-specific environment and is therefore only available in a beamer presentation. Whereas the latter has other applications and is available in all document-classes.
Machine Learning vs. Natural Language Processing, part 1 - Lexalytics (Note: Updated July 2, 2015) What is Machine Learning? Machine Learning (in the context of text analytics) is a set of statistical techniques for identifying some aspect of text (parts of speech, entities, sentiment, etc). Troubleshooting Sweave The purpose of Sweave is to make statistical analyses reproducible. However, technical difficulties can keep the Sweave document from being itself reproducible. Here are some things that could go wrong. These notes are based on my experience using Sweave on Windows XP using R version 2.4.1 and MiKTeX version 2.5. Session contamination Top four LaTeX mistakes Here are four of the most common typesetting errors I see in books and articles created with LaTeX. 1) Quotes Quotation marks in LaTeX files begin with two back ticks, ``, and end with two single quotes, ''. The first “Yes” was written as ``Yes.'' in LaTeX while the one with the backward opening quote was written as