Learn how to use H2O Cloud AI Developer Services to build, automate, and share AI solutions for your business needs. This course covers key services across tabular data, language tasks, computer vision, and developer tools.
You’ll explore practical workflows, including AutoML for tabular data, NLP with Hydrogen Torch, data labeling with Label Genie, and using AI assistants for coding tasks.
By the end, you’ll know how to apply H2O Cloud AI Developer Services to real-world AI projects across different domains.
What you'll learn
Tabular AI Services
Learn to use AutoML for tabular data, handle large datasets, and connect to diverse data sources.
Vision AI Services
Label data with Label Genie, work with document AI, and develop computer vision models.
Language AI Services
Build and deploy NLP solutions using tools like Hydrogen Torch and customize models for enterprise use cases.
AI Assistants for Developers
Boost productivity with AI code suggestions and automations designed for developers.
Course Playlist on YouTube
In this playlist, we'll explore how H2O AI Cloud services empower software engineers, data engineers, and AI developers to streamline AI development within their organizations.
From tabular to language and vision services, we'll delve into the offerings tailored for flexibility and accessibility, whether it's hosted on-premises or as a fully managed solution by H2O.
Let's dive in and discover the tools that can revolutionize your AI development journey.
This video marks the beginning of a series introducing our suite of H2O Cloud AI Developer Services.
The H2O AI cloud offers a suite of services designed to assist software engineers, data engineers, and AI developers in building, automating, monitoring, and sharing AI within their organizations.
During this video, you will see a walkthrough of using H2O's AutoML services for tabular use cases, demonstrating steps from data visualization to model training, interpretation, and deployment using H2O MLOps. Here's an overview of what H2O offers in terms of tabular services:
- Accessibility: Services are accessible regardless of the developer's location, whether hosted on-premises or as a fully managed solution.
- AutoML with Driverless AI: Streamlines model building through automated processes like data visualization, optimization, customization, and scoring pipeline creation.
- Scalability: AI engine instances can be scaled to accommodate varying model sizes and types.
- Data Connectivity: Users can easily connect and upload data from multiple sources such as S3 Amazon buckets, H2O Drive, Snowflake, or H2O Feature Store.
Overall, we aim the video aims to showcase how H2O AI cloud and its services can empower AI developers in efficiently building and deploying AI solutions within their organizations.
In this video, we'll delve into the landscape of language models and the tools that H2O.ai provides to empower developers and researchers alike.
🔍 What You'll Discover:
- Enterprise Use Cases: Discover how Enterprise h2oGPTe is bridging the gap between cutting-edge research and real-world applications, offering a flexible platform for enterprise solutions tailored to specific needs.
- Customization and Deployment: Dive into the customization options and deployment flexibility offered by H2O.ai's language services, enabling users to tailor models to their unique requirements and deploy them seamlessly.
- Evaluation and Annotation Tools: Learn about H2O Eval Studio and H2O Label Genie, essential tools for evaluating model performance and annotating data, crucial steps in the development lifecycle of AI systems.
- Advanced Applications with Hydrogen Torch: Explore the capabilities of Hydrogen Torch, a versatile platform for chaining state-of-the-art GAN networks in computer vision, audio processing, and natural language understanding.
In this video we delve into the intersection of AI and computer vision. We'll uncover the powerful tools and technologies developed by H2O.ai to revolutionize the way we approach data labeling, image classification, and model deployment.
🔍 What You'll Learn:
- Label Genie: Discover how Label Genie, H2O.ai's collaborative annotation tool, utilizes zero-shot generative AI and clustering techniques to streamline data labeling tasks for natural language processing and computer vision projects. See firsthand how clustering helps accelerate the labeling process, making it more efficient and accurate.
- Hydrogen Torch: Explore the capabilities of Hydrogen Torch, H2O.ai's no-code deep learning platform, as we showcase its advanced computer vision capabilities. Witness completed experiments and learn about model training, validation insights, and deployment, providing valuable insights into the model development lifecycle.
- Document AI: Uncover the potential of Document AI, H2O.ai's engine for document classification and extraction. Follow along as we create a demo project, apply optical character recognition (OCR), and train a token labeling model to extract key information from documents, demonstrating the versatility and effectiveness of Document AI.
🚀 Why It Matters:
In today's rapidly evolving landscape of AI and computer vision, H2O.ai's Vision Services offer invaluable tools and technologies for developers, researchers, and AI enthusiasts alike. By simplifying complex tasks such as data labeling, model training, and document analysis, H2O.ai empowers users to unlock the full potential of AI and drive innovation across diverse industries.
H2O.ai provides a diverse array of tools meticulously crafted to enhance your developer experience and facilitate fluid navigation through the Cloud AI Developer Services. Let us delve deeper into the offerings provided by H2O.ai:
- AI Code Assistant in Notebook Lab: Seamlessly transition between programming languages, pose inquiries, and streamline code optimization effortlessly.
- H2O Functions (now called H2O Actions): A versatile agent-based solution designed to tackle challenges in AI and data science domains, enabling coding, experimentation, and beyond.
- Data Upload and Analysis: Effortlessly upload data, conduct analyses, and glean insights with minimal effort.
- GenAI AppStudio: Harness the capabilities of generative AI to craft tailor-made AI applications customized to your requirements, leveraging text prompts or sketches.
Discover further functionalities, including specialized code assistants utilizing Enterprise H2OGPTe or open-source H2OGPT, facilitating seamless interaction with documentation resources.
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Intro to the H2O Cloud AI Developer Services Course
Principal Data Scientist at H2O.ai, specializing in leading complex Machine Learning projects from ideation to production, with a keen interest in Model Ops and a strong background in statistics.
Her expertise covers a broad range of industries such as insurance, energy, and services, enabling her to communicate effectively with both technical and non-technical stakeholders.
Holding a Master of Science in Mathematics and Statistics from Université Aix-Marseille II, Audrey has a proven track record of enhancing business strategies and objectives through data analysis and model development across various data science roles.
Jon Farland
Director of Solutions Eng.
Jon Farland is the Director of the H2O.ai Solutions Engineering team. He has spent the better part of the last decade building analytical solutions at the intersection of technology, finance and energy. He has used H2O extensively to develop high performing models, communicate findings across stakeholders and to lead ROI growth from data science initiatives.
Learn Hands On
Follow structured learning paths designed to build real, production-ready AI skills. Learn at your own pace, practice on real environments, and validate your knowledge through certification.
