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Machine learning and its use in IoT

Machine learning is a technique by which a computer learns to compute a task without explicit instruction. This technique is used to train computers by using algorithms that iteratively learn from data and enable them to find insight. The core subarea of artificial intelligence, it can be used to teach computers to complete a task, make accurate predictions or behave intelligently.

Machine learning is the study of algorithms that improve their performance at some task with experience,” Jeff Smith, Managing Partner at Quantum IoT said during a presentation at the Enterprise IoT Summit, which took place in Austin, Texas, earlier this year. “Machine learning is also the optimization of a criterion using example data or past experience,” he added.

Smith also highlighted that machine learning is primarily concerned with the accuracy and the effectiveness of the computer system. This technique has several related fields including databases, statistics, data mining, control theory, decision theory, cognitive science, and neuroscience, among other, the executive said.

In the past decade, machine learning has helped support self-driving cars, speech recognition, web search optimization and an improved understanding of the human genome. Machine learning is not a new concept, but it is being used in new ways to enable the Internet of Things (IoT)

According to SAS Insights, a number of industries are currently using machine learning and IoT to optimize processes:

Health care

Wearable devices and sensors can use data to assess a patient’s health in real time. The technology can also help medical experts analyze data to identify trends or red flags that may lead to improved diagnoses and treatment.

Marketing and sales

Websites recommending items you might like based on previous purchases are using machine learning to analyze buying history and promote other items you’d be interested in.

Oil and gas

Finding new energy sources, analyzing minerals in the ground, predicting refinery sensor failure, etc.

Transportation

Analyzing data to identify patterns and trends is key to the transportation industry, which relies on making routes more efficient and predicting potential problems to increase profitability.

According to Moor Insights and Strategy, machine learning will exist in a large number of solutions and will account for a great deal of the innovation in the IoT world by 2020 with companies like IBM, with Watson IoT; or Google and TensorFlow leading the way.

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