Overview: H2O Hydrogen Torch

Name: Overview: H2O Hydrogen Torch
Uploaded: 2022-03-18
Duration: 8 min
Description: A walkthrough of H2O Hydrogen Torch, deep learning for image, text, and audio data, using object detection to find weed heads in agricultural images.

Predictive AI
H2O Hydrogen Torch

Overview

This video walks through H2O Hydrogen Torch, H2O.ai's platform for deep learning on image, text, and audio data, using an image object detection use case to identify weed heads in agricultural images. It covers importing data from S3, Kaggle, or direct upload, configuring dataset settings by problem type, and creating experiments with adjustable settings by experience level, from novice to master.

Key takeaways

How to import a dataset into Hydrogen Torch from S3, Kaggle, or direct upload, and configure problem-type-specific settings
How to verify a dataset loaded correctly using sample visualizations and data statistics
How to create an experiment, choose an experience level from novice to master, and use grid search to test setting combinations
What backbone, fold, loss function, and validation metric settings control during experiment setup
How to read experiment results, including the loss chart, metrics tab, confusion matrix, and validation prediction insights
How to generate predictions on new data and download logs, predictions, or a Python/MOJO scoring pipeline

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