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By Ramesh Radhakrishnan
With the rapid advance of the Internet of Things, mobile applications and other emerging technologies, organizations are creating data at speeds and volumes never before imagined. To convert this data into fuel that powers the business, IT and business leaders need sophisticated software tools that allow them to leverage the technologies for artificial intelligence — like those from H20.ai.
H2O.ai is the creator of H20, a leading machine learning and artificial intelligence platform trusted by hundreds of thousands of data scientists and more than 18,000 enterprises around the world. H20 is a fully open‑source distributed in‑memory AI and machine learning software platform with linear scalability. It supports some of the most widely used statistical and ML algorithms — including gradient boosted machines, generalized linear models, deep learning and more.
H2O is also incredibly flexible. It works on bare metal, with existing Apache Hadoop or Apache Spark clusters. It can ingest data directly from HDFS, Spark, S3, Microsoft Azure Data Lake and other data sources into its in‑memory distributed key value store. To further simply AI, H2O has leading-edge AutoML functionality that automatically runs through algorithms and their hyperparameters to produce a leaderboard of the best performing models. And under the hood, H2O takes advantage of the computing power of distributed systems and in‑memory computing to accelerate ML using industry parallelized algorithms, which take advantage of fine‑grained in‑memory MapReduce.
Applications that leverage the H20 software platform include Sparkling Water, which allows users to combine the fast, scalable ML algorithms of H2O with the capabilities of Spark, and H2O Driverless AI. H2O Driverless AI delivers a wide assortment of features to boost data scientist productivity including automatic feature engineering, model validation, model tuning, model selection and deployment, machine learning interpretability, time-series and automatic pipeline generation for model scoring.
It provides companies with an extensible customizable data science software platform that addresses the needs of a variety of use cases. Those who work with Driverless AI can also leverage ‘bring your own recipe’ to take advantage of Intel-optimized libraries for machine learning, drastically reducing training time for XGBoost models on large datasets.
To help organizations get the greatest value from H20.ai software, Dell Technologies and Intel worked with H20.ai to create engineering-validated reference architectures that remove complexity and uncertainty from the AI development process. These architectures enable IT teams to deploy H20 solutions with the confidence that comes with a proven compute foundation for AI and ML workloads that are now critical for advancing business objectives.
The components of these jointly engineered reference architectures include enterprise-class products from Dell Technologies, Intel and H20.ai:
For added flexibility, Dell Technologies Reference Architectures for H2O.ai use a flexible building‑block approach to system design, where individual building blocks can be combined to build a system that’s optimized specifically for unique workloads and use cases.
The bottom line
H2O.ai aims to make machine learning more accessible by automating data science processes and allowing business users to extract insights from data, without requiring expertise in deploying or tuning ML models.
To help organizations capitalize on this opportunity, Dell Technologies, Intel and H20.ai offer engineering-validated reference architectures for the H20 platform. With the guidance of these reference architectures, IT teams can confidently leverage a combination of Dell EMC servers, storage and networking together with H2O.ai software to unleash the power of AI.