March 16th, 2022

Data Science with H2O.ai: An Introduction to Machine Learning and Predictive Modeling

RSS icon RSS Category: Data Science, H2O, H2O AI Cloud, Machine Learning

Our own Jonathan Farland recently recorded a talk about machine learning and predictive modeling. In his talk, Jon also gave an overview of open source H2O and H2O AI Cloud. This video is a great resource for getting up to speed with the latest technology from H2O in half an hour.

Some of you may prefer to go through the slides while listening to the talk. You can find the slides and some screenshots of the software demo below with timestamps. (Note: If the timestamp link doesn’t work, right-click and open it in a new tab.)

Individual Slides

What is Machine Learning? [1:10]

Data Science Project Lifecycle [2:49]

Common Machine Learning Problems [5:26]

Supervised Learning – Regression [6:55]

Supervised Learning – Classification [8:55]

Unsupervised Learning [10:09]

H2O-3 Machine Learning Platform [11:16]

H2O Open Source Tools [12:10]

H2O AI Cloud [13:28]

H2O AI Cloud Demo [16:55]

App Store [17:05]

Driverless AI – AutoViz [22:57]

Driverless AI – Custom Visualization [25:03]

Driverless AI – Experiment [25:38]

Driverless AI – Pipeline Visualization [32:10]

Automatic Documentation [33:19]

 Learning Resources

How to Get Started

You can get hands-on experience with all these tools right now on H2O AI Cloud. Just sign up for a free 90-day free trial today.

About the Author

H2O.ai Team

At H2O.ai, democratizing AI isn’t just an idea. It’s a movement. And that means that it requires action. We started out as a group of like minded individuals in the open source community, collectively driven by the idea that there should be freedom around the creation and use of AI.

Today we have evolved into a global company built by people from a variety of different backgrounds and skill sets, all driven to be part of something greater than ourselves. Our partnerships now extend beyond the open-source community to include business customers, academia, and non-profit organizations.

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