To reap the full benefits of ML, organizations must also mitigate the considerable risks it presents. This report outlines a set of actionable best practices for people, processes, and technology that can enable organizations to innovate with ML in a responsible manner. Authors Patrick Hall, Navdeep Gill, and Ben Cox focus on the technical issues of ML as well as human-centered issues such as security, fairness, and privacy. The goal is to promote human safety in ML practices so that in the near future, there will be no need to differentiate between the general practice and the responsible practice of ML.

After a successful experience in Marketing working for various software providers such as Aptean and Avolin, Eve-Anne is excited to join H2O.ai as EMEA Field Marketing Manager. In her previous roles, Eve-Anne was in charge of planning and running Marketing programs for different solutions of the companys' portfolios and across several regions in order to generate leads, increase sales pipeline, build brand awareness and increase customer engagement. Eve-Anne is French, but was born and raised in Germany, she did part of her studies in Belgium and in London, which gave her a passion for multiculturality and foreign languages. She holds a bachelor's degree in translation and a master's in marketing, and was also recently certified in Project Management. In her spare time, Eve-Anne enjoys traveling, photography and CrossFit.

Ellen is Technical Evangelist at H2O.ai. She is an international speaker, author, and scientist with a PhD in biochemistry from Rice University. Ellen has been a committer for Apache Drill and Apache Mahout projects and previously a laboratory researcher in molecular biology. In addition to authoring publications in technical fields from genetics to oceanography, she is co-author of data-related books published by O'Reilly Media, including AI & Analytics in Production, Machine Learning Logistics, Streaming Architecture, Introduction to Apache Flink and the Practical Machine Learning series. Ellen has been an invited speaker for keynotes at JFokus in Stockholm, Big Data London, the University of Sheffield Methods Institute (UK) and NoSQL Matters in Barcelona as well as invited talks at Nike Tech Talks (Portland OR), Berlin Buzzwords and Strata Data conferences in San Jose CA and London.

October 7, 2020 - Business, Community, Driverless AI, Machine Learning - Accelerating AI Transformation in Healthcare

At H2O.ai, it is our goal to democratize AI by bridging the gap between the State-of-the-Art (SOTA) in machine learning and a user-friendly, enterprise-ready platform. We have been working tirelessly to bring the SOTA from Kaggle competitions to our enterprise platform Driverless AI since its very first release. The growing list of Driverless AI features and our growing team of Kaggle Grandmasters and industry expert data scientists can be seen as our effort and commitment to achieve that goal. Today, we are excited to announce the availability of our latest Driverless AI release 1.9 which comes with tons of new features. This article is the first of the 1.9 release blog series.

Spark is an up and coming new big data technology; it's a whole lot faster andeasier than existing Hadoop-based solutions. H2O does state-of-the-art MachineLearning algorithms over Big Data – and does them Fast. We are happy toannounce that H2O now has a basic integration with Spark – Sparkling Water! This is a "deep" integration – H2O can convert Spark RDDs to H2O DataFrames andvice-versa directly. The conversion is fully in-memory and in-process, anddistributed and parallel as well.

H2O is an open-source, in-memory platform for distributed, scalable machine learning. With the major release 3.30.0.1, released in Q1 2020, H2O obtained first class Kubernetes support. This article explains how to create H2O deployment on Kubernetes. It also covers the selected H2O internal mechanisms for the reader's better understanding of H2O's behavior on Kubernetes cluster. In order to understand the behavior and limitations of H2O distributed cluster, it is mandatory to understand the basics of H2O design.

AI is an important resource to help glean insight in data, forecast patterns and make critical decisions that save lives. H2o.ai brings the power of AI to your organization by providing data scientists a glimpse at what's coming, allowing preparation to start now. Then contrast that with what's happening in real time to learn what is and isn't working. Get answers on every level from individual clinics and hospitals to the entire system, putting you in the know and giving you more of the most important resources: enough time to make a difference.

At H2O.ai, we believe that our strength is rooted in our open source background and machine learning components that are effectively an industry standard, with many other platforms integrating them. We believe we have built on the strength of our open source offering with an innovative Automatic Machine Learning platform with rich explainability functionality, H2O Driverless AI. As the vendor with the strongest completeness of vision of the 16 vendors evaluated in Gartner's 2020 Magic Quadrant for Data Science and Machine Learning Platforms, H2O.ai continues to drive the AI industry forward and accelerate AI adoption in the enterprise with its innovation, roadmap and vision. February 2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms, Peter Krensky, Pieter den Hamer, Erick Brethenoux, Jim Hare, Carlie Idoine, Alexander Linden, Svetlana Sicular, Farhan Choudhary, 11 February 2020 Disclaimer: This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from H2O.ai.

Credit Suisse's DTR Program recognizes the top companies who are disrupting traditional IT with new, visionary, and innovative approaches. "At Credit Suisse, technology innovation is key to providing the best user experience and for our customers and partners," said David Patten, CIO of Credit Suisse's IBCM Division at Credit Suisse AG. "The DTR program was created to recognize the companies that are disrupting the status quo in IT with great products and a clear vision in their respective spaces. H2O.ai is a clear leader in the AI and machine learning space, and continues to push the boundaries on what is possible with these technologies, and helps us deliver high-quality services to our clients." "H2O.ai is honored to be selected into the coveted Credit Suisse's DTR program this year. We are democratizing AI and the trusted partner in the AI transformation of world's leading and sophisticated companies like Credit Suisse," said Sri Ambati, CEO and Founder at H2O.ai.