Machine Learning, a subset of the field of artificial intelligence, uses statistical techniques to give computer systems the ability to learn from datasets without being explicitly programmed. One of the first big breakthroughs in Machine Learning (ML) was in the 1950s when a computer “learned” how to play checkers and then beat the reigning (human) world champion of checkers. Machine Learning continued to gain traction in the 1980s and, today, it's part of our daily existence in ways you probably don't even realize.Many of the apps we use on a daily basis use Machine Learning in the background to create a better user experience. Here are a few examples of how ML impacts our daily lives through the technology we use and consume.
Machine Learning is also critical to the rise of the Internet of Things (IoT). The data collected through sensors and other connected devices is then fed into machine learning models that provide insights on everything from how to optimize package delivery to improvements in patient-centered care. If you are interested in tapping into the power of ML, here is excellent advice on building the business case for ML and the team you’ll need to hire to successfully execute. Most importantly, Machine Learning should be approached with the user experience in mind. For a deep dive into UX and Machine Learning, check out the Slideshare below. [embed]https://www.slideshare.net/SmashingBoxes/ux-and-machine-learning[/embed]What's your favorite app that uses machine learning?
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Five healthcare and technology experts shed light on critical industry trends during Wednesday’s #TriangleTechSpeakerSeries.
Machine Learning, a subset of the field of artificial intelligence, uses statistical techniques to give computer systems the ability to learn from datasets without being explicitly programmed.
The growth of IoT continues to influence life-changing advancements in the Internet of Medical Things (IoMT). Here are 7 informative stats on IoMT.