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Build machine learning models with H2O: linear models, random forests, GBMs, deep learning and unsupervised algorithms, then evaluate and pick the best model under business constraints.
Learn how AI agents combine LLMs, tools, and memory in h2oGPTe, with GAIA benchmark results, industry demonstrations, deployment caveats, and safety guardrails.
Build production-ready enterprise generative AI on h2oGPTe: retrieval-augmented generation, Python integration, H2O Wave apps, and autonomous agent workflows.
Build LLM skills across three levels: fundamentals, data preparation, fine-tuning, and advanced techniques, using H2O.ai tools like LLM DataStudio, h2oGPT, and EvalGPT.
Learn what language models are, how transformer architecture works, and how pre-training, fine-tuning, and transfer learning adapt LLMs to domain-specific applications across industries.
Label text, image, and audio data with H2O Label Genie: build annotation workflows, export annotations, explore datasets, and apply zero-shot labeling and LLM integration.
Build enterprise AI solutions with H2O GPTe: AI-powered search, advanced RAG techniques, LLM agents, Python API automation, and AI-driven web apps in H2O Wave.
Use H2O's toolset to prepare and visualize data, automate model building with Driverless AI, deploy models, and explore generative AI with h2oGPT and Enterprise GPTe.
Prepare datasets for H2O Driverless AI: tabular formats, defining the unit of analysis, automating preprocessing with Python customization, and splitting time series data with date columns.
Explore H2O Cloud AI services to build, automate and share AI solutions: AutoML on tabular data, Hydrogen Torch language and vision models, Label Genie labeling, and code assistants.
Apply AutoML with H2O Driverless AI: set up the environment, import and explore data, run experiments, hyper-tune models, interpret results, and build custom recipes.
Build custom GPT models with h2oGPT and H2O LLM Studio, prepare data with LLM DataStudio, evaluate models with EvalGPT, and deploy AI web apps via GenAI AppStudio.
Explore H2O's GenAI platform in depth: data preparation techniques, advanced model training, deployment strategies, and real-time monitoring across the ecosystem's tools and applications.
Build deep learning models for computer vision, NLP, and audio without coding: import datasets, run experiments, and tune hyperparameters with grid search in Hydrogen Torch.
Build browser-based AI apps with H2O Wave in Python: set up the environment, deploy to H2O AI Cloud, add a GPTe-powered YouTube chatbot, publish to the Gen App Store.
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