H2O Driverless AI

Democratizing AI with Automated Machine Learning

H2O Driverless AI

Delivers industry leading autoML capabilities specifically designed to use AI to make AI, with automation encompassing data science best practices across key functional areas like data visualization, feature engineering, model development and validation, model documentation, machine learning interpretability and more.

Intelligent feature transformation

H2O Driverless AI automates the entire feature engineering process to include detecting relevant features in a given dataset, finding the interactions within those features.

Automated model development

Reducing the time that it takes to develop accurate, production-ready models is critical to delivering AI at scale. H2O Driverless.

Comprehensive explainability toolkit

H2O Driverless AI provides robust interpretability of machine learning models to explain AI results. With industry-leading capabilities for understanding.

Expert recommender system

H2O Driverless AI uses an AI Wizard that investigates your data, provides recommendations based on your business requirements and gives instructions on the appropriate machine learning.

MAKE WITH H2O.ai

Everyone can benefit from the power of artificial intelligence, but only those with certain skill sets have the capacity to build and develop solutions with the machine learning tools available in today’s technology market.

How it works

Connect

Ingest data from a variety of data sets including Hadoop HDFS, Amazon S3, and more.

Transform

Automatically visualize and address data quality issues with advanced feature engineering that transforms your data into an optimal modeling dataset.

Build

Quickly create and test highly accurate and robust models with state-of-the-art automated machine learning that spans the entire data science lifecycle and can process a variety of data types within a single dataset.

Validate

Assess model robustness and mitigate risks in production by obtaining a holistic view of the models and preventing failures on new data.

Explain

Easily understand the ‘why’ behind model predictions to build better models and provide explanations of model output at a global level (across a set of predictions) or at a local level (for an individual prediction).

Advise

Create and customize machine learning models with a built-in guidance system designed to implement data science best practices based on your unique dataset and use case requirements.

Deploy

With H2O Driverless AI, models can be deployed automatically across a number of environment choices including creating a REST endpoint for any web applications to invoke the model, automatically run as a service in the cloud, or simply as a highly optimized Java code for edge devices.

Democratizing AI Adoption with AutoML

As organizations look to streamline decision making and improve customer experiences with AI, they are running into three core challenges of talent, time, and trust.

Data Scientists

Make highly accurate machine learning models with speed and transparency to accelerate the implementation of analytic initiatives.

H2O Driverless AI empowers data scientists to work on projects faster and more efficiently by using automation to accomplish key machine learning tasks in just minutes or hours, not months. By delivering automatic feature engineering, model validation, model tuning, model selection and deployment, machine learning interpretability, bring your own recipe, time-series and automatic pipeline generation for model scoring, H2O Driverless AI provides companies with an extensible customizable data science platform that addresses the needs of a variety of use cases for every enterprise in every industry.

2 business analysts looking at content on 6 screens

DevOps and IT Professionals

Operationalize models with minimal changes to existing workflows.

With H2O Driverless AI, machine learning models can be deployed automatically across a number of environment choices including creating a REST endpoint for any web applications to invoke the model, automatically run as a service in the cloud, or simply as a highly optimized Java code for edge devices. It is optimized to work with the latest Nvidia GPUs, IBM Power 9 and Intel x86 CPUs and to take advantage of GPU acceleration to achieve up to 30X speedups for automated machine learning. H2O Driverless AI includes support for GPU accelerated algorithms like XGBoost, TensorFlow, LightGBM GLM, and more.

Devops engineer sitting at desk with IDE open

Business Analysts

Driverless AI users can take advantage of the flexibility it offers in the feature engineering process via built-in recipes, an open catalog of recipes and by using BYO functionality.

H2O Driverless AI allows almost everyone within a business to create their own predictive models. The quality of models generally depends on the skills and experience of data scientists involved. Once the user defines a target column, Driverless AI will automatically identify the appropriate features, select and parameterize the optimal algorithm, present the results in chart format and enable the user to automatically deploy the new model to production.

Data Scientists
DevOps and IT
Business Analysts

CASE STUDIES

H2O Driverless AI in Action

Trusted by the World’s Most Regulated Industries

I am very excited to use the H2O Driverless AI because prior to it, we used to spend weeks hyperparameter tuning etc., but with Driverless AI, one experiment takes just a few hours.

Wei Shao

Data Scientist, Hortifrut

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AI to do AI is absolutely a watershed moment in our industry.

Martin Stein,

Chief Product Officer, G5

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The automation of the data science process reduced time and costs. And time is money. So, you can do more with the same amount of time. It's possible to deliver more value to the business, develop more use cases and focus the data science effort in the use case instead of development tasks.

Ruben Diaz

Data Scientist, Vision Banco, Vision Banco

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