Applied Language Technology

A brief introduction to JupyterLab

Cloning repositories from GitHub

Exploring Jupyter Notebooks

Getting started with Python: variables and objects

How to make the most of the learning materials

Text formats and encoding

Sentence segmentation using spaCy

Manipulating text in Python: join a list into a string

Saving and loading pandas DataFrames

Introduction to the CoNLL-U annotation schema

Named Entity Recognition (NER) using spaCy

Extending pandas DataFrames

Introduction to word embeddings in spaCy

Evaluating performance: accuracy, precision, recall and F1-score

Writing spaCy annotations to disk

Nominals in the Universal Dependencies framework

Customizing spaCy pipelines

Parsing and visualising syntactic dependencies using spaCy

Welcome to Applied Language Technology

Interfacing the spaCy and Stanza libraries using spacy-stanza

Tokenizing text using spaCy

Loading data into pandas DataFrames

Working with multiple files

Regular expressions

Working with files and directories using pathlib

Training a neural network for learning word embeddings

Introducing Stanza: how to download language models and load them into the library

Creating a neural network for learning word embeddings

Parsing CoNLL-U annotations using Python

Creating a spaCy Doc object manually

Manipulating text in Python: replace, split and pop