In this video, we'll review Cloud Vision's capabilities to analyze images and extract information.
- [Instructor] Cloud Vision is a prebuilt…innate analytic service available…through the Google Cloud Platform.…It is the same internal platform that Google uses…to do its own innate analytics.…Cloud Vision can analyze images and extract metadata,…like file names, time stamps, and location…about these images.…It supports a REST API, through which…image analytics requests can be initiated,…and response received back through JSON.…
The key use case for Cloud Vision…is to classify images based on its content.…It can identify image types,…recognize faces with images,…and also read printed words within these images.…It also supports document classification,…when the documents are in PDF or TIFF formats.…It can extract text from these documents,…and then we can use them for text analytics.…A key use case for image analytics…is to understand content and classify and moderate them.…
Adult or obscene content can be identified and classified…through Cloud Vision.…It can be used for automatically validating content…that is uploaded by users.…
Author
Kumaran Ponnambalam
Released
11/7/2018- Evaluating the machine learning tools in GCP
- Understanding the predictive analytics process
- Building models
- Training models with jobs
- Building and running predictions
- Best practices for cost control, testing, and performance monitoring
Skill Level Intermediate
Duration
Views
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Introduction
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1. ML Options in GCP
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Cloud Dataproc56s
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Cloud ML Engine1m 37s
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Cloud Natural Language1m 20s
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Cloud Translation1m 17s
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Cloud Vision1m 18s
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Cloud Video Intelligence1m 2s
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Cloud Dialogflow1m 14s
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2. Cloud ML Basics
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Models56s
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Model versions41s
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Jobs56s
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Predictive analytics process1m 55s
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3. Model Building with Cloud ML
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Understanding input data1m 30s
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Build and test model locally1m 53s
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Modify code to work with GCP1m 42s
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Creating a training package1m 21s
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Training using jobs3m 49s
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4. Predictions in Cloud ML
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Creating a model version2m 10s
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Running a prediction1m 37s
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5. Cloud ML Best Practices
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Cost control1m 17s
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Local testing1m 12s
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Performance monitoring1m 35s
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Conclusion
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Next steps41s
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Video: Cloud Vision