Major strides in artificial intelligence (AI)–especially in the subset of machine learning–have exceeded expectations in the past few years. In January 2016, for instance, Google’s DeepMind created AlphaGo, which beat the ancient Chinese game Go 10 years before experts predicted it would.

These major achievements have spurred businesses to take advantage of machine learning tools for the enterprise that can support their use of data. Instead of relying on programming, machine learning algorithms can “teach” computer systems to identify patterns and make predictions based on massive data sets.

In September 2016, Google officially dubbed its cloud technologies for the enterprise Google Cloud, and offered a host of new cloud technologies and machine learning tools as part of the package.

So why is building a machine learning platform important for the enterprise? This comprehensive guide explores the technology behind, and business implications of, Google Cloud Machine Learning.

SEE: Check out all of TechRepublic’s smart person’s guides

Executive summary

  • What is Google Cloud Machine Learning Engine? It is a tool that enables businesses to build machine learning models to better understand their data and make predictions using it.
  • Why does Google Cloud Machine Learning Engine matter? Machine learning models have advanced significantly in the last several years, due to advanced computing power that can handle a significant amount of data–which, itself, has exploded with the growth of the Internet of Things (IoT) and other devices.
  • Who does Google Cloud Machine Learning Engine affect? The service is currently used by businesses such as Airbus, Home Depot, Snap Inc. (formerly SnapChat), and Evernote, but is available for businesses of all sizes across multiple industries.
  • When is Google Cloud Machine Learning Engine available? Google Cloud Machine Learning Engine was officially announced in September 2016.
  • How can I take advantage of Google Cloud Machine Learning? Google’s Cloud Machine Learning service is available for businesses to try for free.

SEE: Special report: How to implement AI and machine learning (free PDF) (TechRepublic)

What is Google Cloud Machine Learning Engine?

Google Cloud Machine Learning Engine is a NoOps machine learning solution that businesses can use to build and train large-scale machine learning models. As ZDNet has reported, it integrates with data analytics and storage cloud services such as Google BigQuery and Cloud Dataflow. Businesses can also learn more through Google’s dedicated machine learning educational and certification programs. According to Google, the service can handle multiple scenarios, from building regression models to image classification.

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Why does Google Cloud Machine Learning Engine matter?

Harnessing the power of AI is essential for businesses to remain competitive, reports TechRepublic’s Alison DeNisco, citing that “By 2019, 40 percent of all digital transformation initiatives will be supported by cognitive/AI capabilities, according to IDC.” Machine learning algorithms give businesses the ability to stay cutting-edge, making use of and gleaning intelligence from large amounts of data.

Google and other companies, such as Amazon, IBM, Microsoft, and others, offer open source AI platforms, which DeNisco says is where “most of the AI innovation is happening.”

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Who does Google Cloud Machine Learning Engine affect?

Google Cloud Machine Learning Engine affects businesses by helping them efficiently analyze and glean insights from data, and customers, who can take advantage of streamlined services that use the tools, such as chatbots. Companies like Airbus, Home Depot, Snap Inc. (formerly SnapChat), Evernote, Niantic Labs, Telus, Accenture, and Pivotal are currently using the service. And, according to Google, “Accenture has integrated the Google Cloud Platform into the Accenture Cloud Platform and will support the use of Google tools in industries like healthcare, retail, energy, and finance.”

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When is Google Cloud Machine Learning Engine available?

Machine learning, which rose to prominence in the 1990s, has seen a recent growth in interest. Here are some timeline highlights, from TechRepublic’s smart person’s guide on machine learning:

  • 2011: Google Brain–a deep neural network that could identify and categorize objects–was created.
  • 2014: Facebook’s DeepFace algorithm was introduced, which could recognize people from a set of photos.
  • 2015: Amazon launched its machine learning platform, and Microsoft offered a Distributed Machine Learning Toolkit.
  • 2016: Google’s DeepMind program AlphaGo beat the world champion, Lee Sedol, at the complex game of Go.

Google Cloud Machine Learning Platform is available today.

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