HP Service Brings Machine Learning to Mainstream Developers

Yet another effort to democratize notoriously difficult Big Data analytics was announced yesterday by Hewlett Packard Enterprise, which is providing a machine learning (ML) service to bring that advanced technology to mainstream developers.

The company yesterday announced its HPE Haven OnDemand Machine Learning-as-a-Service (MLaaS) has become commercially available after a December 2014 beta launch that attracted more than 12,750 registered developers who have helped fine-tune the service.

"HPE Haven OnDemand democratizes Big Data by bringing the power of machine learning, traditionally reserved for high-end, highly trained data scientists, to the mainstream developer community," said exec Colin Mahony. "Now, anyone can leverage our easy to use cloud-based service to harness the rich variety of data available today to build applications that produce new insights, differentiate businesses, delight customers and deliver competitive advantage."

In the face of esoteric data science skills and advanced implementation knowledge needed for sophisticated analytics initiatives -- combined with a lingering skills shortage -- HPE Haven OnDemand is one of many industry efforts to simplify the technology.

The platform features more than 60 advanced ML APIs and services to help developers build data-driven applications including mobile, enterprise, consumer, desktop and Internet of Things (IoT) projects. The APIs provide capabilities such as "prediction, face-detection, speech-to-text, and knowledge graph analysis for a wide range of data formats, including text, audio, image, social, Web and video," the company said.

Face Recognition with HPE Haven OnDemand
[Click on image for larger view.] Face Recognition with HPE Haven OnDemand (source: Hewlett Packard Enterprise)

HPE Haven OnDemand is a freemium service offered atop the Microsoft Azure Cloud, which lets developers easily try out enterprise-grade ML without much investment or obligation, the company said.

"The software industry is on the cusp of a new era of breakthroughs, driven by machine learning that will power data-driven applications across all facets of life," Mahony said.

The company listed the following capabilities of the service:

  • Advanced text analysis extracts the key meaning from language by employing concept extraction capabilities that go beyond traditional approaches to obtain key concepts, entities and sentiment from text sources.
  • Format conversion provides key functions to access, extract and convert information wherever it lives by supporting a set of standard file formats and the ability to employ optical character recognition to extract text from an image.
  • HPE Haven Search OnDemand enterprise-search-as-a-service delivers cultivated search across on-premise or cloud data to deliver context-sensitive search results.
  • Image recognition and face detection enables applications to detect specific image features and code around human-centric use cases to identify the gender of an individual or key information such as a brand logo from within an image.
  • Knowledge graph analysis automatically delivers insights and predictions related to relationships and behavioral patterns among people, places and things. These capabilities are useful for analyzing social media and related data.
  • Predict and recommend enables developers to view patterns in business data to optimize business performance and build a set of self-learning functions that analyze, predict and alert based on structured datasets.
  • Speech recognition employs advanced neural network technology to transcribe speech to text from video or audio files with support for more than 50 languages.

"Since our Beta launch in 2014, we've met with thousands of developers who have used the Haven OnDemand platform to make some truly amazing applications," the company said in a blog post. "It has been inspiring to see the creativity of the Haven OnDemand developer community, now more than 12,000 strong! Along the way, you have told us what you think and we've taken notes and made changes to make the platform more useful, scalable, and reliable."

Pricing details are here.

About the Author

David Ramel is an editor and writer for Converge360.