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Version: v0.3.0

Tutorials

Learn how to rapidly generate labeled datasets supported in H2O Hydrogen Torch

Overview​

The H2O Label Genie tutorials are divided into three major areas:

note

To learn how H2O Label Genie can help annotate data to build and deploy a model with H2O Hydrogen Torch and H2O MLOps, refer to the following blog: In the H2O AI Cloud, build, deploy, and score a state-of-the-art image classification model, starting with unlabeled data.

Text annotation tasks​

  • Tutorial 1A: Annotation task: Text classification

    This tutorial describes the process of annotating and specifying an annotation task rubric for a text classification annotation task. To highlight the process, we are going to annotate a dataset that contains user reviews (in text format) and ratings (from 0 to 5) of Amazon products. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

  • Tutorial 2A: Annotation task: Text regression

    This tutorial underlines the steps (process) of annotating and specifying an annotation task rubric for a text regression annotation task. To highlight the process, we are going to annotate a dataset that contains user reviews (in text format) and ratings (from 0 to 5) of Amazon products. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

  • Tutorial 3A: Annotation task: Text-entity recognition

    This tutorial underlines the steps (process) of annotating and specifying an annotation task rubric for a text-entity recognition annotation task. To highlight the process, we are going to annotate a dataset that contains user reviews (in text format) and ratings (from 0 to 5) of Amazon products. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

  • Tutorial 4A: Annotation task: Text summarization

    This tutorial underlines the steps (process) of annotating and specifying an annotation task rubric for a text summarization annotation task. To highlight the process, we are going to annotate a dataset that contains human-generated abstract summaries from news stories published on the Cable News Network (CNN) and Daily Mail websites. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

Image annotation tasks​

  • Tutorial 1B: Annotation task: Image classification

    This tutorial describes the process of annotating and specifying an annotation task rubric for an image classification annotation task. To highlight the process, we are going to annotate a dataset that contains images of cars and coffee. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

  • Tutorial 2B: Annotation task: Image regression

    This tutorial annotates a dataset that enables you to understand the process of annotating and specifying an annotation task rubric for an image regression annotation task. To highlight the process, we are going to annotate a dataset that contains images of healthy and diseased apple leaves for plant pathology recognition. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

  • Tutorial 3B: Annotation task: Object detection

    This tutorial describes the process of annotating and specifying an annotation task rubric for an object detection annotation task. To highlight the process, we are going to annotate a dataset that contains images of cars and coffee. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

  • Tutorial 4B: Annotation task: Image instance segmentation

    This tutorial describes the process of annotating and specifying an annotation task rubric for an image instance segmentation annotation task. To highlight the process, we are going to annotate a dataset that contains images of cars and coffee. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

Audio annotation tasks​

  • Tutorial 1C: Annotation task: Audio classification

    This tutorial describes the process of annotating and specifying an annotation task rubric for an audio classification annotation task. To highlight the process, we are going to annotate a dataset that contains 5-second-long recordings of environmental sounds organized into ten classes (with 40 examples per class). Clips in this dataset have been manually extracted from public field recordings gathered by the Freesound.org project. This tutorial also explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

  • Tutorial 2C: Annotation task: Audio regression

    This tutorial underlines the steps (process) of annotating and specifying an annotation task rubric for an audio regression annotation task. To highlight the process, we are going to annotate a dataset containing 600 audio samples of spoken digits (0-9) of sixty different speakers. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

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