With the rising prevalence of big data and analytics, AI has quickly become a buzzword for industry practitioners as many businesses are realizing that competitive success lies in the utilization of their unique data through methods such as AI
Once thought to be a luxury afforded only by the largest conglomerates, recent developments such as H20 driverless AI is making it easier than ever for smaller organizations to make use of this technology. As a result, It has become increasingly easy to adopt and innovate with these techniques or programs. But with the numerous AI and machine learning programs cropping up, it is increasingly difficult to choose one for your organization.
H20 AI is an open source machine learning program aimed at providing users with an accessible program that does not compromise speed or accuracy. Featuring Machine learning capability, automatic scoring pipelines and Auto Feature Engineering/ Model Building. H20 features a full suite of powerful programs designed to fit the needs of a variety of industries.
Faster and easier AI development at scale
While traditional models can take weeks or months to reach production, H2O’s Driverless AI creates ultra-low latency automatic scoring pipelines for easy deployment. In addition, H2O supports training, testing and model versioning so that data science and business teams can work together to bring models from data science to production in minutes, not months.
Need community support?
Due to its open source nature, there is a community of over 12,000 organisations and 129,000 data scientists all using H20. This large community means that it’s easy to find information documentation regarding a large variety of issues, topics, and applications of the product itself. This flexibility means that the only limitation is your imagination
AutoViz – Exploratory Data Analysis for Big Data
H2O Driverless AI AutoViz automatically creates data plots based on the most relevant data statistics to help users understand data prior to starting the model building process. This is helpful for data scientists and data engineers who want to better understand the composition of very large data sets and see trends or possible issues that could impact modelling results.
Automatic Feature Engineering and Model Building
Feature engineering is the secret weapon that advanced data scientists use to extract the most accurate results from algorithms. H2O Driverless AI employs a library of algorithms and feature transformations to automatically engineer new, high-value features for a given data set. Included in the interface is an easy to read variable importance chart that shows the significance of original and newly engineered features.
Machine Learning Interpretability (MLI)
H2O Driverless AI provides robust interpretably of machine learning techniques and results. In the MLI view, four charts are generated automatically including K-LIME, Variable Importance, Decision Tree and Partial Dependence. Each helps to explore the modeling techniques and results more closely and these techniques are crucial for those who must explain their models to regulators or customers.
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