An AWS product H2O: predicts fraud and stops it in its tracks powered by Miri Infotech. H2O is open-source software for big-data analysis. It is produced by the start-up H2O.ai (formerly 0xdata), which launched in 2011 in Silicon Valley. The speed and flexibility of H2O allow users to fit hundreds or thousands of potential models as part of discovering patterns in data. With H2O, users can throw models at data to find usable information, allowing H2O to discover patterns. Using H2O, Cisco estimates each month 20 thousand models of its customers' propensities to buy.
We are configuring and publishing H2O embedded pre-configured tool with Python and ready-to-launch AMI on Amazon EC2 that contains Python and H2O.
H2O's mathematical core is developed with the leadership of Arno Candel; after H2O was rated as the best "open-source Java machine learning project" by GitHub's programming members, Candel was named to the first class of "Big Data All Stars" by Fortune in 2014.The firm's scientific advisors are experts on statistical learning theory and mathematical optimization.
The H2O software runs can be called from the statistical package R and other environments. It is used for exploring and analyzing datasets held in cloud computing systems and in the Apache Hadoop Distributed File System as well as in the conventional operating-systems Linux, macOS, and Microsoft Windows. The H2O software is written in Java, Python, and R. Its graphical-user interface is compatible with four popular browsers: Chrome, Safari, Firefox, and Internet Explorer.
Features:
Best of Breed Open Source Technology
Enjoy the freedom that comes with big data science powered by open source technology. H2O was written from scratch in Java and seamlessly integrates with the most popular open source products like Apache Hadoop® and Spark™ to give customers the flexibility to solve their most challenging data problems.
Easy-to-use WebUI and Familiar Interfaces
Set up and get started quickly using either H2O’s intuitive web-based Flow graphical user interface or familiar programming environments like R, Python, Java, Scala, JSON, and through our powerful APIs. Models can be visually inspected during training, which is unique to H2O.
Data Agnostic Support for all Common Database and File Types
Easily explore and model big data from within Microsoft Excel, R Studio, Tableau and more. Connect to data from HDFS, S3, SQL and NoSQL data sources. Install and deploy anywhere, in the cloud, on premise, on workstations, servers or clusters.
Massively Scalable Big Data Analysis
Train a model on complete data sets, not just small samples, and iterate and develop models in real-time with H2O’s rapid in-memory distributed parallel processing.
Real-time Data Scoring
Rapidly deploy models to production via plain-old Java objects (POJO) or model-optimized Java objects (MOJO). Score new data against models for accurate predictions in any environment. Enjoy faster scoring and better predictions than any other technology.
Scalability + Speed
Fine-Grain Distributed Processing on Big Data at Speeds Up to 100x Faster.
In-Memory Processing Responsiveness
With H2O, your organization can harness the responsiveness of highly optimized in-memory processing, so you can operationalize many more models and gain real-time intelligence in business transactions and interactions.