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How This AI Tool Breathes New Life Into Data Science
How This AI Tool Breathes New Life Into Data Science
by h2oai October 16, 2018 Beginners Data Journalism Data Science Deep Learning Driverless Explainable AI GPU H2O Driverless AI Machine Learning NLP Python R Technical

Ask any data scientist in your workplace. Any Data Science Supervised Learning ML/AI project will go through many steps and iterations before it can be put in production. Starting with the question of “Are we solving for a regression or classification problem?” Data Collection & Curation Are there Outliers? What is the Distribution? What do […]

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H2O’s AutoML in Spark
H2O’s AutoML in Spark
by Jakub Hava July 23, 2018 AutoML Sparkling Water Technical Tutorials

This blog post demonstrates how H2O’s powerful automatic machine learning can be used together with the Spark in Sparkling Water. We show the benefits of Spark & H2O integration, use Spark for data munging tasks and H2O for the modelling phase, where all these steps are wrapped inside a Spark Pipeline. The integration between Spark […]

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FfDl cloud hardware
H2O-3 on FfDL: Bringing deep learning and machine learning closer together
by Vinod Iyengar June 25, 2018 Community Deep Learning H2O Technical

This post originally appeared in the IBM Developer blog here. This post is co-authored by Animesh Singh, Nicholas Png, Tommy Li, and Vinod Iyengar. Deep learning frameworks like TensorFlow, PyTorch, Caffe, MXNet, and Chainer have reduced the effort and skills needed to train and use deep learning models. But for AI developers and data scientists, […]

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Machine for peneteration
Scalable Automatic Machine Learning: Introducing H2O’s AutoML
by Erin LeDell June 21, 2017 AutoML Ensembles H2O Release Technical

Prepared by: Erin LeDell, Navdeep Gill & Ray Peck In recent years, the demand for machine learning experts has outpaced the supply, despite the surge of people entering the field. To address this gap, there have been big strides in the development of user-friendly machine learning software that can be used by non-experts and experts, […]

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All data stays on GPU
H2O announces GPU Open Analytics Initiative with MapD & Continuum
by Vinod Iyengar May 8, 2017 Community GPU Technical Technical Posts

H2O.ai, Continuum Analytics, and MapD Technologies have announced the formation of the GPU Open Analytics Initiative (GOAI) to create common data frameworks enabling developers and statistical researchers to accelerate data science on GPUs. GOAI will foster the development of a data science ecosystem on GPUs by allowing resident applications to interchange data seamlessly and efficiently. […]

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Model building for sparkling water
Use H2O.ai on Azure HDInsight
by h2oai April 18, 2017 Cloud Sparkling Water Technical Tutorials

This is a repost from this article on MSDN. We’re hosting an upcoming webinar to present you how to use H2O on HDInsight and to answer your questions. Sign up for our upcoming webinar on combining H2O and Azure HDInsight. We recently announced that H2O and Microsoft Azure HDInsight have integrated to provide Data Scientists […]

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spark_tables
Sparkling Water on the Spark-Notebook
by Vinod Iyengar April 10, 2017 Guest Posts Sparkling Water Technical

This is a guest post from our friends at Kensu. In the space of Data Science development in enterprises, two outstanding scalable technologies are Spark and H2O. Spark is a generic distributed computing framework and H2O is a very performant scalable platform for AI. Their complementarity is best exploited with the use of Sparkling Water. […]

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ensemble
Stacked Ensembles and Word2Vec now available in H2O!
by Erin LeDell February 8, 2017 Data Munging Ensembles H2O Release NLP Python R Technical

Prepared by: Erin LeDell and Navdeep Gill Stacked Ensembles H2O’s new Stacked Ensemble method is a supervised ensemble machine learning algorithm that finds the optimal combination of a collection of prediction algorithms using a process called stacking or “Super Learning.” This method currently supports regression and binary classification, and multiclass support is planned for a […]

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Start Off 2017 with Our Stanford Advisors
Start Off 2017 with Our Stanford Advisors
by Wendy Wong January 9, 2017 Community Technical

We were very excited to meet with our advisors (Prof. Stephen Boyd, Prof. Rob Tibshirani and Prof. Trevor Hastie) at H2O.AI on Jan 6, 2017. Professors Boyd, Tibshirani & Hastie in the house! @h2oai #elementsofstatisticallearning #MachineLearning pic.twitter.com/FnlCNrY7Hy — H2O.ai (@h2oai) January 6, 2017 Our CEO, Sri Ambati, made two great observations at the start of the meeting: […]

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isax_sshot
Indexing 1 Billion Time Series with H2O and ISax
by h2oai November 11, 2016 Technical Tutorials Use Cases

At H2O, we have recently debuted a new feature called ISax that works on time series data in an H2O Dataframe. ISax stands for Indexable Symbolic Aggregate ApproXimation, which means it can represent complex time series patterns using a symbolic notation and thereby reducing the dimensionality of your data. From there you can run H2O’s […]

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