Word of the Day: machine learning

Word of the Day Daily updates on the latest technology terms |June 30, 2017

machine learning Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output value within an acceptable range. Machine learning algorithms are often categorized as being supervised or unsupervised. Supervised algorithms require humans to provide both input and desired output, in addition to furnishing feedback about the accuracy of predictions during training. Once training is complete, the algorithm will apply what was learned to new data. Unsupervised algorithms do not need to be trained with desired outcome data. Instead, they use an iterative approach called deep learning to review data and arrive at conclusions. Unsupervised learning algorithms are used for more complex processing tasks than supervised learning systems. The processes involved in machine learning are similar to that of data mining and predictive modeling. Both require searching through data to look for patterns and adjusting program actions accordingly. Many people are familiar with machine learning from shopping on the internet and being served ads related to their purchase. This happens because recommendation engines use machine learning to personalize online ad delivery in almost real time. Beyond personalized marketing, other common machine learning use cases include fraud detection, spam filtering, network security threat detection, predictive maintenance and building news feeds. Facebook's News Feed, for example, uses machine learning to personalize each member's feed. If a member frequently stops scrolling to read or "like" a particular friend's posts, the News Feed will start to show more of that friend's activity earlier in the feed. Behind the scenes, the software is simply using statistical analysis and predictive analytics to identify patterns in the user's data and use those patterns to populate the News Feed. Should the member no longer stop to read, like or comment on the friend's posts, that new data will be included in the data set and the News Feed will adjust accordingly. Quote of the Day "Machine learning is a powerful tool, but you can cut yourself. You may have a model that looks like it works, but later you find its predictions are bogus." - Zoiner Tejada   Trending Terms AI data mining predictive analytics deep learning neural network predictive modeling   Learning Center Machine learning platforms comparison: Amazon, Azure, Google, IBM There are many machine learning platforms today, but choosing the right one is tough. Use this chart to learn about your options. Machine learning systems are a 'land rush' of opportunity for CIOs Machine learning systems are breaking new ground, and CIOs have a chance to do the same, according to MIT superstars Erik Brynjolfsson and Andrew McAfee. A physician-programmer experiments with AI and machine learning in the ER Artificial intelligence and machine learning are coming to the enterprise. One way for CIOs to prepare is to design a flexible architecture. Deep learning vs. machine learning: The difference starts with data While they may seem similar, there are some real differences in deep learning vs. machine learning that can affect analytics applications in businesses. MIT aims to pry open 'black box' of machine learning systems SystemsThatLearn@CSAIL, a new initiative at MIT, wants to accelerate the development and democratization of machine learning systems. Writing for Business Some employees fear that computers will take over their jobs with the _______ of machine learning, but that is not the case. A. raise B. rise Answer       Stay In Touch For feedback about any of our definitions or to suggest a new definition, please contact me at: mrouse@techtarget.com   Visit the Word of the Day Archives and catch up on what you've missed!   FOLLOW US About This E-Newsletter This e-newsletter is published by the TechTarget network. To unsubscribe from Whatis.com, click here. Please note, this will not affect any other subscriptions you have signed up for. TechTarget, Whatis, 275 Grove Street, Newton, MA 02466. Contact: webmaster@techtarget.com Copyright 2016 TechTarget. All rights reserved.