What is Machine Learning?
Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data. Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data. The process of machine learning is similar to that of data mining. Both systems search through data to look for patterns.
Machine learning is now widely used by many software manufactures. Most of the IT companies are now investing in Machine learning. Developers are working on creating complex algorithms to enhance machine learning in systems and provide more intelligence to end users. Here in this blog we will see five real world examples of machine learning.
1) Word prediction and corrections in Office 365 by Microsoft
Just when you thought Google's AI products are the best, Microsoft strikes back with AI in Microsoft Word that blows away Google Docs. The recent version of office 365 has mind blowing machine learning added in word prediction and corrections. It just don't correct it but it will also learn from your way of writing and learns the words which you use frequently. It's really awesome. You can read more about it on following link.
2) Facebook and Machine Learning
Facebook builds its business by learning about its users and packaging their data for advertisers. It then reinvests this money into offering us new, useful functionality – currently video and shopping - which it also uses to learn even more about us. Facebook achieve its goals of providing greater convenience to users, and enabling them to learn more about us. You can read more at following link.
3) JP Moragan Software COIN
The program, called COIN, for Contract Intelligence, does the mind-numbing job of interpreting commercial-loan agreements that, until the project went online in June, consumed 360,000 hours of work each year by lawyers and loan officers. The software reviews documents in seconds. COIN is just the start for the biggest U.S. bank. The firm recently set up technology hubs for teams specializing in big data, robotics and cloud infrastructure to find new sources of revenue, while reducing expenses and risks. Read more at below link.
4) Google's Self Driving Cars
Google's self-driving cars can tour you around the streets of Mountain View, California. Google has mapped 2,000 miles of road. The US road network has 4 million miles of road. Google's team uses machine learning algorithms to create models of other people on the road. Every single mile of driving is logged, and that data fed into computers that classify how different types of objects act in all these different situations. While some driver behavior could be hardcoded in ("When the lights turn green, cars go"), they don't exclusively program that logic, but learn it from actual driver behavior. You can read more about it on following link.
5) Google Maps use Machine Learning to Predict Parking Difficulty
Google Maps now tackles parking problems as well. Google quietly launched a new parking feature for Google Maps on Android across 25 major US cities. If you are in these metro areas, you will now see a red parking sign that indicates limited parking availability to help you plan your trip. The interesting part of this update is that it does not rely on internet-connected parking meters; which often provide incomplete or wrong information due to illegal parkers or those who depart early from their spot. Instead, Google Maps combined crowdsourced data and relatively simple machine learning algorithms to classify parking difficulty. You can read more about it at following link.
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