Skip to Main Content
Natural Language Processing in Action
book

Natural Language Processing in Action

by Cole Howard, Hobson Lane, Hannes Hapke
April 2019
Intermediate to advanced content levelIntermediate to advanced
544 pages
17h 29m
English
Manning Publications
Content preview from Natural Language Processing in Action

13 Scaling up (optimization, parallelization, and batch processing)

This chapter covers

  • Scaling up an NLP pipeline
  • Speeding up search with indexing
  • Batch processing to reduce your memory footprint
  • Parallelization to speed up NLP
  • Running NLP model training on a GPU

In chapter 12, you learned how to use all the tools in your NLP toolbox to build an NLP pipeline capable of carrying on a conversation. We demonstrated crude examples of this chatbot dialog capability on small datasets. The humanness, or IQ, of your dialog system seems to be limited by the data you train it with. Most of the NLP approaches you’ve learned give better and better results, if you can scale them up to handle larger datasets.

You may have noticed that your computer bogs ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Natural Language Processing with PyTorch

Natural Language Processing with PyTorch

Delip Rao, Brian McMahan

Publisher Resources

ISBN: 9781617294631Supplemental ContentPublisher SupportPublisher WebsiteSupplemental ContentOtherPurchase Link