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H2O.ai logoH2O.ai · Feature trail

H2O-3 Core Platform

5 posts · Jun 2026

What this trail covers

H2O Hydrogen Torch is a no-code deep learning platform for training state-of-the-art models across various data types (text, image, 3D image, video, audio). It democratizes deep learning by allowing users to experiment with hyperparameters, tune models, and achieve high accuracy without coding. Models can be deployed to H2O MLOps or external Python environments. The platform supports a wide range of deep learning problem types including classification, regression, object detection, semantic segmentation, instance segmentation, and metric learning. It integrates with H2O Wave for app development and APIs for broader consumption.

All H2O.ai trails
  1. H2O Hydrogen TorchThis post introduces H2O Hydrogen Torch, a no-code deep learning platform. It details the platform's capabilities for training state-of-the-art models across diverse data types (text, image, 3D, video, audio) and problem types (classification, regression, object detection, segmentation, metric learning). It highlights benefits like democratizing deep learning, speed, and accuracy, and outlines the 'How-it-Works' process: Ingest, Set Up, Train, Inspect, Deploy, and Consume. It also showcases use cases and a success story.
  2. H2O-3This post describes the core H2O-3 open-source distributed in-memory machine learning platform. It details the platform's key features including leading algorithms (GBM, GLM, deep learning, XGBoost, GLRM, Word2Vec), its AutoML functionality for automating model selection and hyperparameter tuning, distributed in-memory processing for scalability and speed, and simple deployment options via POJOs and MOJOs. The post also mentions its ability to run on existing big data infrastructure (Hadoop, Spark, Kubernetes) and ingest data from various sources (HDFS, Spark, S3, Azure Data Lake).
  3. UndatedH2O-3 Secure vs Open SourceThis post introduces H2O-3 Secure as a commercial offering that builds upon H2O-3 OSS. It highlights the added value of enterprise-grade features such as FedRAMP High alignment, audit-supporting capabilities for SOC 2, ISO 27001, and ISO 42001, commercial CVE patching, enterprise SSO, RBAC, and premium support with SLAs. The post emphasizes a seamless upgrade path from H2O-3 OSS, assuring users that their existing code, APIs, and pipelines will remain unchanged.