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Key takeaways
- Jonathan Farland recorded a talk covering machine learning and predictive modeling basics, including supervised regression, supervised classification, and unsupervised learning.
- The talk includes a demo of H2O's platform tools, including the App Store, Driverless AI's AutoViz and custom visualization features, and automatic documentation.
- The talk walks through the H2O-3 open-source machine learning platform and H2O's open source tools before demonstrating the broader platform.
- The post links learning resources for the App Store, Wave Apps, Feature Store, MLOps, Enterprise Steam, Sparkling Water, Driverless AI, Hydrogen Torch, H2O-3, and Document AI.
- Viewers can follow along with individual timestamped slides covering topics from the data science project lifecycle to pipeline visualization in Driverless AI.
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
- H2O AI Cloud
- Product Overview: https://h2o.ai/platform/ai-cloud/
- App Store: https://docs.h2o.ai/h2oappstore/index.html
- Wave Apps: https://docs.h2o.ai/h2o_wave/index.html
- Feature Store: https://docs.h2o.ai/feature_store/index.html
- Architecture
- For serving model endpoints → MLOps: https://docs.h2o.ai/h2o-mlops/index.html
- For provisioning new clusters → Enterprise Steam: https://docs.h2o.ai/steam/index.html
- For running on existing Spark clusters → Sparkling Water: https://docs.h2o.ai/sw/index.html
- AI Engine
- Driverless AI: https://docs.h2o.ai/dai/index.html
- Hydrogen Torch: https://docs.h2o.ai/h2o-ht/index.html
- Open Source H2O-3: https://docs.h2o.ai/h2o-3/index.html
- Document AI: https://www.h2o.ai/platform/document-ai/
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 demo today.