Product Owner, Data Scientist, and Kaggle Grandmaster, Mark Landry presented at the Make with H2O.ai session on getting started with H2O Document AI.  The session covered an overview of H2O Document AI, a tool to extract insights and automate document processing. The session also included a product demo, looking at documents as data sets, how […]

According to a report by the High-Level Panel for a Sustainable Ocean Economy, it is estimated that illegal, unreported, and unregulated (IUU) fishing accounts for 20 percent of the seafood and up to 50 percent in some areas. These activities not only affect the marine ecosystem but, in a way, are linked to climate change […]

Note: this is a guest blog post by Jaafar Almusaad. How Much is My Property Worth? This is the million-dollar question – both figuratively and literally. Traditionally, qualified property valuers are tasked to answer this question. It’s a lengthy and costly process, but more critically, it’s inconsistent and largely subjective. Mind you, valuation is an […]

The use cases and the impact of machine learning can be observed clearly in almost every industry and in applications such as drug discovery and patient data analysis, fraud detection, customer engagement, and workflow optimization. The impact of leveraging AI is clear and understood by the business; however, AI systems are also seen as black […]

A paper resulting from a collaboration between H2O.AI and BLDS, LLC was recently published in a special “Machine Learning with Python” issue of the journal, Information (https://www.mdpi.com/2078-2489/11/3/137). In “A Responsible Machine Learning Workflow with Focus on Interpretable Models, Post-hoc Explanation, and Discrimination Testing,” coauthors, Navdeep Gill, Patrick Hall, Kim Montgomery, and Nicholas Schmidt compare model accuracy […]

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 […]

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, […]

Register for the Meetup Here Patients, physicians, nurses, health administrators and policymakers are beneficiaries of the rapid transformations in health and life sciences. These transformations are being driven by new discoveries (etiology, therapies, and drugs/implants), market reconfiguration and consolidation, a movement to value-based care, and access/affordability considerations. The people and systems that are driving these […]

Dear Community, Your intelligence, support and love have been the strength behind an incredible year of growth, product innovation, partnerships, investments and customer wins for H2O and AI in 2017. Thank you for answering our rallying call to democratize AI with our maker culture. Our mission to make AI ubiquitous is still fresh as dawn […]

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 […]