In Part 1 of this series earlier, we looked at how to download data from Lending Club using Jupyter/Python and create a training and test data set, after dropping some target leakage cols. The data preparation code to create the data sets for classification is available in GitHub at: https://git.io/fjTqb In this blog post, we […]

If your business has started using AI/ML tools or just started to think about it, this blog is for you. Whether you are a data scientist, VP of data science or a line of a business owner, you are probably wondering how AI will impact your organization in various ways or why your current strategies […]

It is my pleasure to share with you some never before exposed nuggets and insights from the making of H2O Driverless AI, our latest automatic machine learning product on our mission to democratize AI. This has been truly a team effort, and I couldn’t be more proud of our brilliant makers who continue to relentlessly […]

We just launched the H2O.ai Academic Program at our sold-out H2O World London. With nearly 1000 people in attendance, we received the first online sign-up forms submitted by professors and students alike. This program will massively democratize AI in academia, increasing the number of AI-skilled graduates – with both technical and business degrees. A short […]

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 (e.g. H2O, scikit-learn, keras). Although these tools have made it easy to train and evaluate machine learning […]

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 […]

Hi Makers! There are several new features in the latest Sparkling Water. The major new addition is that we now publish Sparkling Water documentation as a website which is available here. This link is for Spark 2.2. We have also documented and fixed a few issues with LDAP on Sparkling Water. Exact steps are provided […]

Wolpert Release (H2O 3.18) There’s a new major release of H2O and it’s packed with new features and fixes! We named this release after David Wolpert, who is famous for inventing Stacking (aka Stacked Ensembles). Stacking is a central component in H2O AutoML, so we’re very grateful for his contributions to machine learning! He is […]

In today’s market, there aren’t enough data scientists to satisfy the growing demand for people in the field. With many companies moving towards automating processes across their businesses (everything from HR to Marketing), companies are forced to compete for the best data science talent to meet their needs. A report by McKinsey says that based […]

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, […]