Introduction As part of my role within the automated machine learning space with H2O.AI and Driverless AI, I have seen that many times people struggle to find the right optimization metric for their data science problems. This process is even more challenging in regression problems where the errors are often not bounded like you normally have with probabilistic modeling. […]

Last updated: 09/06/19 Steve Jobs once said, “A lot of times, people don’t know what they want until you show it to them’. This makes sense, especially in this era of constant choice overload. Consumers today have access to a plethora of products just at the click of their mouse. These innumerable choices can sometimes […]

Recently, while shopping for a laptop bag, I stumbled upon a pretty amusing customer review: “This is the best laptop bag ever. It is so good that within two months of use, it is worthy of being used as a grocery bag.” The innate sarcasm in the review is evident as the user isn’t happy […]

Lending Club publishes its basic loan databases to the public and a full version to its customers — anonymized of course. You can find the download page from this link (screenshot below): The publicly downloadable loan data has various attributes — roughly 150+ columns that have categorical, numeric, text and date fields. It also has a ‘loan_status’ text column […]

Creating and plotting decision trees (like one below) for the models created in H2O will be the main objective of this post: Figure 1. Decision Tree Visualization in R Decision Trees with H2O With release 3.22.0.1 H2O-3 (a.k.a. open source H2O or simply H2O) added to its family of tree-based algorithms (which already included DRF, […]

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 […]

Introducing Accelerated Automatic Pipelines in H2O Driverless AI At H2O, we work really hard to make machine learning fast, accurate, and accessible to everyone. With H2O Driverless AI, users can leverage years of world-class, Kaggle Grand Masters experience and our GPU-accelerated algorithms (H2O4GPU) to produce top quality predictive models in a fully automatic and timely […]

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 […]

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 […]

TensorFlow on AWS GPU instance In this tutorial, we show how to setup TensorFlow on AWS GPU instance and run H2O Tensorflow Deep learning demo. Pre-requisites: To get started, request an AWS EC2 instance with GPU support. We used a single g2.2xlarge instance running Ubuntu 14.04.To setup TensorFlow with GPU support, following softwares should be […]