© Ekaba Bisong 2019
Ekaba  BisongBuilding Machine Learning and Deep Learning Models on Google Cloud Platformhttps://doi.org/10.1007/978-1-4842-4470-8_43

43. Google AutoML: Cloud Natural Language Processing

Ekaba Bisong
(1)
OTTAWA, ON, Canada
 
This chapter will build a language toxicity classification model to classify and recognize toxic and non-toxic or clean phrases using Google Cloud AutoML for natural language processing (NLP). The data used in this project is from the Toxic Comment Classification Challenge on Kaggle by Jigsaw and Google. The data is modified to have a sample of 16,000 toxic and 16,000 non-toxic words as inputs to build the model on AutoML NLP.

Enable AutoML NLP on GCP

The following steps will enable AutoML NLP on GCP:
  1. 1.
    Click the ...

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