In this lesson, you will learn how to organise a set of texts into a corpus and perform some basic linguistic analysis using the Voyant Tools platform.| programminghistorian.org
This lesson demonstrates how to prepare a geographically accurate historical battle scene in the free and open source computer game 0̸ A.D. You will learn to use a multisensory, interacti...| programminghistorian.org
This lesson demonstrates how to visualize data through choropleth maps using Python and the Folium library. It discusses common problems encountered with choropleth maps and explains how to add interactive elements and save the maps for sharing.| Programming Historian
After reviewing the basic principles and challenges of radiocarbon dating, this lesson teaches you how to use the R programming language to calibrate a set of dates, and then explore and present...| programminghistorian.org
This lesson shows how to create interactive web-based dashboards using Python's Dash library. Using two news media case studies, this lesson provides a practical guide for making digital humanities research outputs more accessible and engaging.| Programming Historian
This lesson demonstrates how to use R's ggplot2 package to create sophisticated data visualizations through a 'grammar of graphics' framework. Using historical data about European sister-city relationships in the post-second world war period, including partnerships, population sizes, and geographic distances, the lesson guides readers through the process of creating various plots while exploring urban and demographic patterns.| Programming Historian
This lesson will introduce the core concepts, methodologies and discussions surrounding simulation methods for historical inquiry. You will learn the basics of programming a simulation model by building an Agent-Based Model of historical letter exchanges using the Python library mesa.| Programming Historian
This lesson covers tokenization, part-of-speech tagging, and lemmatization, as well as automatic language detection, for non-English and multilingual text. You’ll learn how to use the Python packages NLTK, spaCy, and Stanza to analyze a multilingual Russian and French text.| Programming Historian
Jupyter notebooks provide an environment where you can freely combine human-readable narrative with computer-readable code. This lesson describes how to install the Jupyter Notebook software, ho...| programminghistorian.org
This is the first of a two-part lesson introducing deep learning based computer vision methods for humanities research. Using a dataset of historical newspaper advertisements and the fastai Pyth...| programminghistorian.org
In this lesson you will install QGIS software, download geospatial files like shapefiles and GeoTIFFs, and create a map out of a number of vector and raster layers.| programminghistorian.org
Introduces core concepts of Linked Open Data, including URIs, ontologies, RDF formats, and a gentle intro to the graph query language SPARQL.| programminghistorian.org
In this lesson, you will use R-language to analyze and map geospatial data.| programminghistorian.org
This tutorial teaches users how to use the Edinburgh Geoparser to process a piece of English-language text, extract and resolve the locations contained within it, and plot them as a web map.| programminghistorian.org
Researchers often need to be able to search a corpus of texts for a defined list of terms and historians are often interested in certain places named in a text or texts. This lesson details how ...| programminghistorian.org
This lesson will teach you how to use Python to extract a set of keywords very quickly and systematically from a set of texts.| programminghistorian.org
In this lesson, you will learn how to download YouTube video comments and use the R programming language to analyze the dataset with Wordfish, an algorithm designed to identify opposing ideologi...| programminghistorian.org
In this lesson, you’ll learn computer vision and machine learning principles for object recognition, and how to apply these principles using Python to recognize and classify smiling faces in his...| programminghistorian.org
A digital gazetteer records information associated with specific places. This lesson teaches you how to create a gazetteer from a historical text, using the Linked Places Delimited (LP-TSV) format.| programminghistorian.org
This lesson demonstrates how to use nanDECK to design and publish your own deck of printed or digital playing cards, and use them to test a group's knowledge of historical events through a _Time...| programminghistorian.org
Word embeddings allow you to analyze the usage of different terms in a corpus of texts by capturing information about their contextual usage. Through a primarily theoretical lens, this lesson wi...| programminghistorian.org
This lesson demonstrates how to create interactive data visualizations in Python with Plotly's open-source graphing libraries using materials from the Historical Violence Database.| programminghistorian.org
Tools for machine transcription of handwriting are practical and labour-saving if you need to analyse or present text in digital form. This lesson will explain how to write a Python program to t...| programminghistorian.org
This lesson demonstrates how to use the Python library spaCy for analysis of large collections of texts. This lesson details the process of using spaCy to enrich a corpus via lemmatization, part...| programminghistorian.org
This lesson uses word embeddings and clustering algorithms in Python to identify groups of similar documents in a corpus of approximately 9,000 academic abstracts. It will teach you the basics o...| programminghistorian.org
Google Vision and Tesseract are both popular and powerful OCR tools, but they each have their weaknesses. In this lesson, you will learn how to combine the two to make the most of their individu...| programminghistorian.org
This lesson teaches you how to obtain and analyse narrative texts for patterns of sentiment and emotion.| programminghistorian.org
This lesson introduces basic use of Map Warper for historical maps. It guides you from upload to export, demonstrating methods for georeferencing and producing visualizations.| programminghistorian.org
This lesson introduces Uniform Resource Locators (URLs) and explains how to use Python to download and save the contents of a web page to your local hard drive.| programminghistorian.org
In this lesson you will learn how to manipulate text files using Python.| programminghistorian.org
Learn how to perform OCR and text extraction with free command line tools like Tesseract and Poppler and how to get an overview of large numbers of PDF documents using topic modeling.| programminghistorian.org
This lesson will help you set up an integrated development environment for Python on a computer running the Windows operating system.| programminghistorian.org
In this lesson you will learn how to visually explore and present data in Python by using the Bokeh and Pandas libraries.| programminghistorian.org
This lesson introduces you to HTML and the web pages it structures.| programminghistorian.org
In this lesson you will learn how to create vector layers based on scanned historical maps.| programminghistorian.org
Demonstrates how to use the JavaScript library| programminghistorian.org
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