Review how to use AutoML Vision to create custom label output for photos.
- Let's look a bit little more deeply…at AutoML using the Vision example.…So here we have on the left side,…some images that you'll be using…with AutoML to create your model.…Notice that there are labels around these images,…unlike using the Vision API where you simply…upload photos and Google provides the labels.…When you work with AutoML you need to provide the labels.…This data that's uploaded is then used…to train a model that Google selects.…
So model training, tuning, deployment…and scaling is all handled by Google.…As part of the model process you'll be provided…with evaluation information, so that you can understand…if your model is performing at a level,…in other words identifying or labeling…new images properly at a level that…is appropriate to your business.…Let's dive in to labeling because this is so important…in working with any of the AutoML services…and we'll use Vision as an example.…
So for Vision in order to create any type…of a model you must have 10 examples or 10 images…per label, it's recommended that you…
- Hosting options: Serverless, containers, and virtual machines
- Enabling the GCP ML AIs
- Preparing data with Cloud Dataflow and Dataprep
- Modeling predictions for images, video, text to speech, and cloud translation
- Machine learning with AutoML
- Advanced machine learning and deep learning
- Machine learning architectures
Skill Level Intermediate
1. Machine Learning on Google Cloud Platform
2. Machine Learning API Services
3. Machine Learning with AutoML
Understand AutoML Vision4m 57s
4. Advanced Machine Learning
5. Machine Learning Architectures
Next steps1m 30s
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