Driverless AI – Introduction, Hands-On Lab and Updates

#H2OWorld was an incredible experience. Thank you to everyone who joined us!

There were so many fascinating conversations and interesting presentations. I’d love to invite you to enjoy the presentations by visiting our YouTube channel.

Over the next few weeks, we’ll be highlighting many of the talks. Today I’m excited to share two presentations focused on Driverless AI – “Introduction and a Look Under the Hood + Hands-On Lab” and “Hands-On Focused on Machine Learning Interpretability”.

Slides available here.

Slides available here.

The response to Driverless AI has been amazing. We’re constantly receiving helpful feedback and making updates.

A few recent updates include:

Version 1.0.11 (December 12 2017)
– Faster multi-GPU training, especially for small data
– Increase default amount of exploration of genetic algorithm for systems with fewer than 4 GPUs
– Improved accuracy of generalization performance estimate for models on small data (< 100k rows)
– Faster abort of experiment
– Improved final ensemble meta-learner
– More robust date parsing

Version 1.0.10 (December 4 2017)
– Tooltips and link to documentation in parameter settings screen
– Faster training for multi-class problems with > 5 classes
– Experiment summary displayed in GUI after experiment finishes
– Python Client Library downloadable from the GUI
– Speedup for Maxwell-based GPUs
– Support for multinomial AUC and Gini scorers
– Add MCC and F1 scorers for binomial and multinomial problems
– Faster abort of experiment

Version 1.0.9 (November 29 2017)
– Support for time column for causal train/validation splits in time-series datasets
– Automatic detection of the time column from temporal correlations in data
– MLI improvements, dedicated page, selection of datasets and models
– Improved final ensemble meta-learner
– Test set score now displayed in experiment listing
– Original response is preserved in exported datasets
– Various bug fixes

Additional release notes can be viewed here:

If you’d like to learn more about Driverless AI, feel free to explore these helpful links:
– Driverless AI User Guide:
– Driverless AI Webinars:
– Latest Driverless AI Docker Download:
– Latest Driverless AI AWS AMI: Search for AMI-id : ami-d8c3b4a2
– Stack Overflow:

Want to try Driverless AI? Send us a note.