D-Lab's 9 hour introduction to text analysis with Python. Learn how to perform bag-of-words, sentiment analysis, topic modeling, word embeddings, and more, using scikit-learn, NLTK, gensim, and spaCy in Python.

D-Lab's introduction to text analysis with Python. Learn how to preprocess text data, apply bag-of-words methods, engage with word embeddings, and more, using Python. Resources

Mar 21, 2024 · We explore fundamental approaches to applying computational methods to text in Python. We cover some of the major packages used in natural language processing, including scikit-learn, NLTK, spaCy, and Gensim.

Welcome to the Digital Scholarship Lab introduction to Text Analysis with Python class. In this class we'll learn the basics of text analysis: parsing text; analyzing the text; We'll...

Natural Language Toolkit (NLTK) is a leading platform for building Python programs to work with human language data (Natural Language Processing). It is accompanied by a book that explains the underlying concepts behind the language processing tasks supported by the toolkit.

In this workshop, we'll focus fundamental approaches to applying computational methods to text in Python. We'll cover some of the major packages used in natural language processing, including scikit-learn , nltk , and gensim .

Aug 23, 2016 · Students will learn the basics of cleaning, transforming, and formatting text data. They will build corpora, pull specific elements out of text strings, and pull simple metrics from text data, such as word counts and sentiment polarity.

Welcome to the Digital Scholarship Lab introduction to Text Analysis with Python class. In this class we’ll learn the basics of text analysis: parsing text analyzing the text We’ll use our own home made analysis tool first, then we’ll use a python library called TextBlob to …

Find and prepare texts for analysis, tore, access, and document their text objects and data. Discuss their corpus-building decisions and textual data in ways that are methodologically and disciplinarily sound. Identify appropriate text analysis methods for a given question.

May 23, 2016 · Each session will explore a published literary study that has used computational evidence along with close reading. Specifically, we will look at code and practice exercises that reproduce the researchers' method or main finding, while building proficiency with common text analysis methods.