This talk was recorded in London on Oct 30, 2018 and can be viewed here: https://youtu.be/tNK3Fc02jj0 Arno Candel is the Chief Technology Officer at H2O.ai. He is the main committer of H2O-3 and Driverless AI and has been designing and implementing high-performance machine-learning algorithms since 2012. Previously, he spent a decade in supercomputing at ETH and SLAC and collaborated with CERN on next-generation particle accelerators. Arno holds a PhD and Masters summa cum laude in Physics from ETH Zurich, Switzerland. He was named “2014 Big Data All-Star” by Fortune Magazine and featured by ETH GLOBE in 2015. Follow him on Twitter: @ArnoCandel.

1. What’s New in
H2O Driverless AI
Arno Candel
CTO
H2O.ai
@arnocandel

2. Feature v1.0 v1.1 v1.2 v1.3
v1.4
(NOW)
v1.5 v2.0
Kaggle Grandmaster Recipes for i.i.d. data
Automatic Visualization
Machine Learning Interpretability
GBM (XGBoost) for high accuracy incl. stacked ensembles (CPU/GPU)
5-minute Install with Docker for Linux/Mac/Windows - Cloud/OnPrem
Standalone Python Scoring Pipeline
Hardware acceleration: NVIDIA GPUs (DGX-1 etc.)
User Management and Security (LDAP/Kerberos)
Data Connectors: NFS/HDFS/S3/GCS/BigQuery, CSV/Excel/Parquet/Feather
GLM (Linear models) for high interpretability (CPU/GPU)
Native Installer: RPM/DEB
Cloud Neutral: Amazon/Microsoft/Google
Kaggle Grandmaster Recipes for Time-Series
IBM Power8/Power9
AutoDoc
Deep Learning TensorFlow Models (CPU/GPU)
Standalone Java Scoring Pipeline (MOJO)
Deep Learning for NLP / Text (CPU/GPU)
LightGBM Models (CPU/GPU)
Improved Time-Series Recipes (Multiple Windows), MLI for Time-Series
Improved Final Ensemble
Local Feature Brain
C++ Scoring Pipeline
FTRL Models
Multi-Node Training and much more (based on customer demand)
Driverless AI Roadmap

3. H2O Driverless AI 1.4.0

4. Major Changes for 1.4.0
• Speed and Accuracy:
• Added LightGBM (CPU/GPU/MOJO)
• Improved Final Ensemble Stacking (multiple pipelines)
• Feature Brain and Checkpointing
• Time-Series:
• Multiple rolling windows for model validation and tuning
• MLI for Time-Series (Diagnostics and Shapley)
• Auto-generated IsHoliday features
• Time columns detected in Dataset Details
• Many additional features for MLI
• Faster AutoVis
• KDB+ connector, bug fixes and stability improvements

5. 16th (of 2926)
Live Demo