Machine Learning Development: The Future of Innovation

Companies recognize the value of machine learning — recent data shows that 87 percent of organizations have already implemented machine learning or have near-term deployment plans. While 84 percent believe this technology provides a competitive advantage, 60 percent said they lack necessary skills to take full advantage of machine learning solutions.

The result? Spending isn’t enough. Companies must also implement machine learning development strategies to maximize impact and drive innovation.

Line of Business Benefits

The goal of machine learning is to train computers to conduct specific tasks autonomously, learn from the completion of these tasks and then apply this learning to future tasks. Often considered a subset of AI, machine learning is gaining ground as companies look for ways to empower human creativity without sacrificing speed or security.

There’s big potential here for the bottom line: With the right tools in place, companies can speed the process of data discovery, improve pattern recognition and virtually eliminate human error. Soon, highly specialized machine learning tools could be used in conjunction with human oversight to drive innovation and boost corporate productivity.

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Who Is Using the Technology?

Already, multiple industries are leveraging machine learning solutions to improve processes and reduce complexity. Key players include:

  • Finance — Here, machine learning is used to detect and prevent fraud, identify investment opportunities and evaluate potential clients.
  • Healthcare — By combining EMR and IoT patient data, learning tools can identify high-risk trends and develop potential treatment plans.
  • Oil and Gas — Companies are now using machine learning to analyze mineral deposits, proactively predict maintenance needs and streamline distribution.
  • Social media — Sites such as Pinterest leverage this technology to improve content discovery for users, while social media giant Facebook is tapping machine learning solutions to develop chatbots and filter spam content.
  • E-commerce companies — Here, machine learning has the potential to innovate the customer buying experience. By analyzing shopper actions, behaviors and search queries, machine learning solutions can help consumers who don’t know exactly what they’re looking to find what they really want.

Delivering on Machine Learning Potential

How do you get started with machine learning? The right technologies are critical — tools such as Elastic, Docker, ionic and Ruby on Rails all can be paired with learning solutions to help improve app development or enhance existing software functionality.

The caveat? Most organizations aren’t machine learning companies — as noted above, they know the value of this technology but lack the expertise to capitalize on its potential for innovation.

That’s where we come in. At Digital Scientists, we’ve earned a reputation for top-tier custom software development and design — in part thanks to our machine learning consulting services and expertise.

Not sure how to translate machine learning potential into actionable insight for your organization? Wondering how to empower your latest application idea with the ability to learn over time and deliver increasing value? Curious about improving productivity through machine learning techniques? We can help.

Our team of innovation experts has the depth of expertise and breadth of experience you need to capitalize on machine learning solutions today — and drive critical innovation tomorrow. Ready? Let’s talk.

Interested in reading more?  

Check out this case story about a Fortune 500 company wrestling with the need to stay competitive or risk elimination by online retail giant Amazon. 

Read this blog about devices like the Amazon Echo, Google Home, and Apple HomePod that allow users to command them to perform a variety of functions, simply by telling them what to do.