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Classifying 19th Century British Library books using Crowdsourcing and Machine Learning
  • Introduction

Genre Classification

  • Overview of the Project: Classifying British Library Books By Genre
  • Genre Classification
  • Crude Genre Classification

Exploratory Data Analysis

  • Sample Inspector (Part I)
  • Sample Inspector (Part II)

Training our first model

  • Training our first book genre classification model
  • Model inference

Assesing our models performance

  • Improving our model
  • Assessing Where our Model is Going Wrong

Improving our model

  • Creating More Training Data Without More Annotating
  • Using our newly expanded data
  • Fine tuning our fastai model with new data
  • Using a Transformer Based Model

Sharing our results and final inference

  • Sharing our work
  • Using our new Hugging Face model

Further resources

  • Other resources
  • Bibliography
  • Glossary
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Index

C | M

C

  • crowdsourcing

M

  • Microsoft Digitised Books

By Daniel van Strien, Giorgia Tolfo, Victoria Morris, Kaspar Beelen
© Copyright 2021 The Alan Turing Institute, British Library Board, Queen Mary University of London, University of Exeter, University of East Anglia and University of Cambridge..