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Company Overview of H2O.ai
H2O.ai develops an open source parallel processing prediction engine for machine learning and predictive analytics on big data. It offers H2O, an open source predictive analytics platform for data scientists, application developers, and business analysts who need in-memory machine learning for smarter applications. The company also provides marketing mix modeling, risk and fraud analysis, advertising technology, and customer intelligence solutions. H2O.ai was formerly known as 0xdata, Inc. and changed its name to H2O.ai in November 2014. The company was founded in 2011 and is based in Mountain View, California.
1185 Terra Bella Avenue
Mountain View, CA 94043
Founded in 2011
Key Executives for H2O.ai
Co-Founder and Chief Executive Officer
Co-Founder and Chief Technology Officer
Head of Product & Data Science
Director of Customer Experience
Compensation as of Fiscal Year 2014.
H2O.ai Key Developments
H2O.ai Announces New Python API for Sparkling Water
Feb 12 15
H2O.ai announced the availability of the company’s Sparkling Water for Python developers. Through the new API, application developers are now able to harness the power of data science with H2O’s in-memory machine learning and deep learning algorithms to build intelligent applications. For many developers, implementing robust data science methodologies is difficult without an in-house data scientist to develop algorithms to test and train models. Engineers need out of the box power tools to leverage machine learning and deep learning – to build smartness into their business applications. Sparkling Water for Python unifies and extends audience for scalable machine learning. The Python API gives application programmers the tools to rapidly utilize the fast scalable machine learning capabilities within Sparkling Water. Along with the release of the API, Sparkling Water has been updated to include: Native iPython Notebook support for single UI utilization Flow – an augmented iPython Notebook style interactive web interface for CoffeeScript, R and Scala users. Accelerating Python interactive sessions with Sparkling Water, with Spark driving SQL queries - Tighter and transparent integration with H2O's Sparkling Water package so that Spark and Python developers can utilize the ML algorithms in H2O - Feature engineering, Data Munging and math expressions at scale & speed.
H2O.ai Launches Artificial Intelligence Developer Program
Feb 12 15
H2O.ai unveiled a new artificial intelligence (AI) developer program designed to empower engineers with the tools to implement AI and Machine Learning and make their apps smarter. Apps.h2o.ai is designed to support application developers via events, networking opportunities, and a new, dedicated website comprising developer kits and technical specs, news, and product spotlights. These resources will enable developers to sharpen their Machine Learning proficiency and accelerate the deployment of apps with the power and convenience of AI to the lives of consumers and businesses worldwide.
H2O.ai Announces Availability of New Flow and Play Products at H2O World
Nov 19 14
H2O.ai announced the public availability of H2O.Flow and H2O.Play - two unique platforms which increase speed of implementation and data science workflow development. H2O.Flow is a web-based interactive computational environment where the user can combine code execution, text, mathematics, plots and rich media into a single document, much like IPython Notebooks. Unlike traditional interactive computing environments output text, Flow utilizes a "hybrid" user interface that seamlessly blends a command-line shell with a modern point-and-click graphical user interface for every operation in H2O. Flow uniquely simplifies capturing, replaying, annotating, sharing and presenting analysis workflows and uses the bog-standard H2O REST API under the hood; so not only can the user can access and manipulate raw H2O objects under the hood, the user can also build custom GUI applications using H2O's REST API, right from within Flow. H2O.Play presents the first private cloud instance for quickly deploying open source machine learning at petabyte scale that is completely agnostic of the underlying architecture. This allows possible to train predictive models with all of the user data quickly and easily without the overhead of managing hardware and distributed systems. Play also comes preloaded with a range of algorithms, supporting actions across S3, HDFS and local data sets.
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