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An introduction to AutoML
Google Cloud AutoML
Cloud AutoML (https://cloud.google.com/automl/) is a full suite of products
for image, video, and text processing. As of the end of 2019, the suite consists of the
following components, which do not require you to know how the deep learning
networks are shaped internally:
AutoML Tables
• Enables you to automatically build and deploy state-of-the-art machine
learning models on structured data used for general supervised classification
and regression (see chapters 1, 2, and 3).
AutoML Vision
• AutoML Vision: Enables you to train machine learning models to classify
your images according to your own defined labels.
• AutoML Object Detection: Used to automatically build a custom model to
detect objects in an image with bounding boxes and labels, then deploy it to
the cloud or on the edge.
AutoML Natural Language
• AutoML Text Classification: Used to automatically build a machine
learning model to classify content into a custom set of categories.
• AutoML Sentiment Analysis: Used to automatically build a machine
learning model to analyze the sentiment expressed within text.
• AutoML Entity Extraction: Used to automatically build a machine learning
model to recognize a custom set of entities within text.
• Cloud Natural Language API: Use Google's proven pretrained model for
general content classification, sentiment analysis, and entity recognition.
AutoML Video Intelligence
• AutoML Video Intelligence Classification: Used to automatically build a
custom model to classify images, then deploy it to the cloud or on the edge.
AutoML Translation
• AutoML Translation: Build on top of Google's powerful Translation API
with the words, phrases, and idioms that you need.
In the remainder of this chapter we will review five AutoML solutions: AutoML
Tables, AutoML Vision, AutoML Text Classification, AutoML Translation, and
AutoML Video Classification.
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