Come meet the Makers!

NVIDIA’s GPU Technology Conference (GTC) Silicon Valley, March 26-29th is the premier AI and deep learning event, providing you with training, insights, and direct access to the industry’s best and brightest. It’s where you will see the latest breakthroughs in self-driving cars, smart cities, healthcare, high-performance computing, virtual reality and more, and all because of the power of AI. H2O.ai will be there in full force to share how you can immediately gain value and insights from our industry-leading AI and ML platforms. In case you hadn’t heard, H2O.ai was named a leader in 2018 Gartner Magic Quadrant for Data Science and Machine Learning platforms. You can get the report here.

Please visit us at booth #725 to see Driverless AI in action and talk to the Makers leading the AI movement! Our sessions will be leading edge talks that you won’t want to miss.

  1. Ashrith Barthur – Network Security with Machine Learning

    Ashrith will speak about modeling different kinds of cyber attacks and building a model that is able to identify these different kinds of attacks using machine learning.

    Room 210F – Wednesday, 28 March, 9 AM to 9:50 AM.

  2. Jonathan McKinney – World’s Fastest Machine Learning with GPUs

    Jonathan will introduce H2O4GPU, a fully featured machine learning library that is optimized for GPUs with a robust python API that is a drop dead replacement for scikit-learn. He will demonstrate benchmarks for the most common algorithms relevant to enterprise AI and will showcase performance gains as compared to running on CPUs.

    Room 220B – Thursday, March 29, 11 AM to 11:50 AM.

  3. Arno Candel – Hands-on with Driverless AI

    In this lab, Arno will show how to install and start Driverless AI, the automated Kaggle Grandmaster in-a-box software, on a multi GPU box. He will go through the full end-to-end workflow and showcase how Driverless AI uses the power of GPUs to achieve 40x speedups on algorithms that in turn allow it run thousands of iterations and find the best model.

    Room LL21C – Thursday, March 29, 4 PM to 6 PM.

Can’t make it to the event? Schedule a time to talk to one of our makers!

H2O4GPU Hands-On Lab (Video) + Updates

Deep learning algorithms have benefited significantly from the recent performance gains of GPUs. However, it has been uncertain whether GPUs can speed up powerful classical machine learning algorithms such as generalized linear modeling, random forests, gradient boosting machines, clustering, and singular value decomposition.

Today I’d love to share another interesting presentation from #H2OWorld focused on H2O4GPU.

H2O4GPU is a GPU-optimized machine learning library with a Python scikit-learn API tailored for enterprise AI. The library includes all the CPU algorithms from scikit-learn and also has selected algorithms that benefit greatly from GPU acceleration.

In the video below, Jon McKinney, Director of Research at H2O.ai, discussed the GPU-optimized machine learning algorithms in H2O4GPU and showed their speed in a suite of benchmarks against scikit-learn run on CPUs.

A few recent benchmarks include:

We’re always receiving helpful feedback from the community and making updates.

Exciting updates to expect in Q1 2018 include:

  • Aggregator
  • DBSCAN
  • Kalman Filters
  • K-nearest neighbors
  • Quantiles
  • Sort

If you’d like to learn more about H2O4GPU, I invite you to explore these helpful links:

Happy Holidays!

Rosalie