H2O Open Tour Dallas – Slides
Download, share and re-experience the presentations from H2O Open Tour Dallas.
Transformation with Data + AI – Sri Ambati
Top 10 Data Science Practitioner Pitfalls – Mark Landry
Over-fitting, misread data, NAs, collinear column elimination and other common issues play havoc in the day of practicing data scientist. In this talk, Mark Landry, one of the world’s leading Kagglers, will review the top 10 common pitfalls and steps to avoid them.
Deep Learning with MXNet – Dmitry Larko
Dmitry will show the audience on how get started with Mxnet and building Deep Learning models to classify images, sound and text.
Cybersecurity with AI – Ashrith Barthur
Ashrith talks about whether it’s time for the cyber security industry to start using AI to solve their challenges.
What's happening in H2O & Steam – Bill Gallmeister
Bill Gallmeister, VP of Engineering at H2O.ai, shows what’s latest and greatest in H2O & Steam and shares the roadmap.
Deep Water - GPU Deep Learning for H2O – Arno Candel
Deep Water brings the latest and greatest in the Deep Learning space all under the H2O hood. Use Tensorflow, Mxnet & Caffe all from standard H2O interface’s including R, Python & Flow. Also deploy your models easily using the H2O platform.
Sparkling Water 2.0 – Michal Malohlava
Michal Malohlava from H2O.ai talks about the new features in Sparkling Water 2.0 and the future roadmap.
H2O AutoML roadmap – Ray Peck
Ray Peck from H2O.ai talks about the roadmap for the upcoming AutoML product in H2O.
Nvidia Deep Learning Solutions – Alex Sabatier
Alex Sabatier from Nvidia talks about the future of Deep Learning from an chipmaker perspective.
sparklyr – Jeff Allen
Jeff will showcase the sparklyr the new R package to interface with Spark and talk about the different use extensions including the rsparkling ML package.
Skutil - H2O meets Sklearn – Taylor Smith
Skutil brings the best of both worlds to H2O and sklearn, delivering an easy transition into the world of distributed computing that H2O offers, while providing the same, familiar interface that sklearn users have come to know and love.