DataRobot Automated Machine Learning Speeds Time to Value for AI Background V2.0

Automated Machine Learning Speeds Time-to-Value for AI

November 13, 2020
· 2 min read

Businesses of all sizes are working to apply AI to their biggest challenges and most exciting opportunities. But they’re running into a severe headwind: lack of AI talent. In a Gartner survey of 3,000 enterprise CIOs from around the world, 54 percent identified skills shortages as their biggest AI challenge.

To help enterprises move ahead with AI, DataRobot’s automated machine learning (AutoML) platform, running on the latest Intel™ technology, automates many of the tasks needed to develop AI and machine learning applications. That helps data scientists work more efficiently and gives business users the tools to create robust machine learning models using enterprise data and business processes.

DataRobot’s AutoML solution, combined with Intel technology, gives enterprises performance and memory capacity. Using second-gen Intel™ Xeon™ scalable processors and Optane™ persistent memory, businesses can train models on datasets of up to 100GB. Moreover, a system with Intel Optane persistent memory can train up to a 1.33x larger dataset at the same memory cost of a DRAM-only system.

How it works

Using DataRobot’s AutoML product, businesses can automate much of the tedious and time-consuming manual work required by most current data science. With DataRobot and Intel, data-savvy users of all skill levels have access to powerful machine learning algorithms, with best practices and safeguards in place to avoid human error.

With better access to the power of machine learning, businesses can generate advanced machine learning models without the need to understand complex algorithms. Data scientists can apply their special expertise to fine-tune machine learning models for purposes ranging from manufacturing to retailing to healthcare, and more. 

DataRobot’s AutoML is designed for transparency, so users can understand and explain how models were built and why those models make specific predictions. An intuitive GUI and built-in visualizations show which types of data are most useful, delivering insights into what is having a genuine impact on business performance.

Instead of spending weeks or months developing and testing hand-coded models, DataRobot’s AutoML users can build hundreds of models, test them, and deploy the best-performing ones – all within hours. At the same time, data science experts can focus on refining and developing new models so that they can add meaningful business value.

A streamlined path to AI

AutoML from DataRobot, coupled with Intel technology, offers a rapid path to predictive analytics and AI success. It’s an industrial-grade platform that helps users scale their machine learning efforts to complete more projects and explore new uses cases. AI can change a business. AutoML and Intel make it happen.

Want to learn more? Download our white paper “Use Automated Machine Learning to Speed Time-to-Value for AI” and get on the path to unlocking the full power of machine learning.

Use Automated Machine Learning To Speed Time-to-Value for AI

DataRobot + Intel

Download Now

About the author

Value-Driven AI

DataRobot is the leader in Value-Driven AI – a unique and collaborative approach to AI that combines our open AI platform, deep AI expertise and broad use-case implementation to improve how customers run, grow and optimize their business. The DataRobot AI Platform is the only complete AI lifecycle platform that interoperates with your existing investments in data, applications and business processes, and can be deployed on-prem or in any cloud environment. DataRobot and our partners have a decade of world-class AI expertise collaborating with AI teams (data scientists, business and IT), removing common blockers and developing best practices to successfully navigate projects that result in faster time to value, increased revenue and reduced costs. DataRobot customers include 40% of the Fortune 50, 8 of top 10 US banks, 7 of the top 10 pharmaceutical companies, 7 of the top 10 telcos, 5 of top 10 global manufacturers.

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