Overview
This tutorial blog highlights how H2O AI Cloud (HAIC) lets novice and expert data scientists build state-of-the-art machine learning (ML) models by supporting crucial parts of the machine learning life cycle. In particular, this tutorial utilizes H2O Hydrogen Torch and other HAIC applications to build, deploy, and score a state-of-the-art image classification model. This model is capable of determining whether an image depicts a car or coffee (or a cup of coffee). The following applications are utilized:
Application | How this tutorial uses the application | Details of the application |
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H2O Label Genie (v0.3.0) | To label (prepare) the data for the image classification model. | H2O Label Genie expedites the process of labeling data by utilizing zero-shot learning models. |
H2O Hydrogen Torch (v1.3.0) | To build the image classification model. |
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H2O MLOps (v0.60.1) | To deploy the image classification model. | Built H2O Hydrogen Torch models can be deployed to H2O MLOps right from the H2O Hydrogen Torch UI. |