New Innovations in H2O, AutoML and Award-Winning H2O Driverless AI Address Critical Capabilities for Customers
H2O.ai, the open source leader in AI and ML, announced new and innovative capabilities for its data science and machine learning platforms, H2O, AutoML and H2O Driverless AI, to address the critical scalability and performance needs of all organizations. As part of these new capabilities, and to further the company’s mission to democratize AI, H2O.ai has added several new algorithms that address common use cases that customers need today.
In addition, H2O Driverless AI is a winner of InfoWorld’s 2019 Technology of the Year for the second year in a row. The award honors and recognizes the best in software development, cloud computing, big data analytics, and machine learning tools. This year’s judging panel recognized H2O Driverless AI for outpacing all other vendors with “automated simplicity” of its algorithms that do the heavy lifting of feature engineering, model selection, training and optimization – enabling even non-AI experts to uncover hidden patterns using both supervised and unsupervised machine learning.
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According to InfoWorld, “H2O.ai pushed several significant updates in 2018—most importantly for natural language processing, time series prediction, and gradient boosting. Visual decision trees now graphically step users through understanding ‘how’ a prediction was made—to clarify, for example, why an insurance claim was flagged fraudulent. H2O’s visual tools and clear explanations go a long way to bridge understanding across business teams, IT, and data scientists.”
“We are excited that H2O Driverless AI is recognized by InfoWorld as 2019 Technology of the year” said, Sri Ambati, CEO and Founder at H2O.ai. “Thanks to the rapid innovation and adoption of Driverless AI in 2018, some of the world’s most demanding retail and investment banks, hedge-funds, underwriters, retailers and telcos trust H2O Driverless AI to automate their machine learning and AI pipelines. Customer and community feedback inspires last mile innovation at H2O and I couldn’t be prouder of the entire team’s work in building a great product that wins accolades from customers and analysts alike.”
“H2O.ai’s Driverless AI platform harnesses the power of NVIDIA Tensor Core GPUs to enable customers to see significant speedups in automated machine learning to deliver AI insights and interpretability,” said Jeff Herbst, Vice President of Business Development at NVIDIA. “H2O Driverless AI continues to gain momentum as it offers advanced capabilities that solve real world problems for customers today.”
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H2O Driverless AI Innovations
The latest release of its award-winning “AI to do AI” automatic machine learning platform, H2O Driverless AI launched a number of new features including:
- Model checkpointing: This enables customers to re-train models quickly without restarting each time
- Enhanced capability to handle massive workloads: The latest version of Driverless AI improves deployment speed on existing infrastructure while significantly lowering memory footprint
- Support for new algorithms: Along with XGBoost, Tensorflow, GLM and RuleFit, LightGBM and FTRL are the latest supervised algorithms to be added to Driverless AI. It also uses K-Means, SVD, PCA and other unsupervised algorithms for feature engineering. The combination of these algorithms ensures that customers now have more options to solve their data science problems and can address a variety of use cases ranging from credit risk scoring, anti-money laundering, customer churn predictions, fraud detection, cyber threat prevention and more.
The latest version of H2O Driverless AI is available immediately for download and use.
Also at H2O World San Francisco today, H2O.ai announced several new strategic partnerships and technology integrations for H2O Driverless AI with leading organizations, including Intel, Alteryx and Kx.
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New Innovations in H2O, Sparkling Water and AutoML
H2O.ai also announced new innovations of its leading open source platform, H2O, and AutoML which now include new enhancements such as:
- The addition of Isolation Forest algorithm for anomaly detection – which highly effective when solving problems like fraud detection and intrusion detection
- Fully distributed XGBoost in AutoML
- The ability to inspect trees thoroughly for all the tree-based algorithms
- Target encoding of categorical variables for feature engineering
- Monotonicity constraints for GBM
- H2O-3 supports multi-node XGBoost for its H2O Sparkling Water project, as well as Spark 2.4.
H2O World San Francisco
H2O.ai is holding its sold out community event, H2O World San Francisco, a multi-day interactive event featuring deep-dive technical and hands on training, advancements in machine learning and sessions focused on real-world business use cases. With speakers from Alteryx, AI4ALL, IBM, LinkedIn, Microsoft, Stanley Black and Decker, Wells Fargo and more, the conference brings together the brightest minds in AI from across multiple industries to discuss the trends in artificial intelligence, machine learning and data science, important real-world use cases, and the biggest challenges currently facing the industry.
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