6 Use Cases for Machine Learning
Machine learning is the development and implementation of computer programs that enable computers to learn on their own from data instead of being explicitly programmed. As a sub-discipline of computer science, machine learning grew out of the quest for artificial intelligence, and today it is applied in a variety of practical tasks.
Classify and label photos
Yelp hosts tens of millions of photos uploaded by Yelpers from all around the world. To understand what the pictures mean when they are not labeled, Yelp focused initially on sorting photos into a handful of predefined classes. Further, they focused only on categories of photos directly relevant to restaurants such as “food,” “drink,” and “menu.” Using photos labeled by users as “training data,” the machine learning system has achieved 94% precision in classifying correctly photos that were not previously labeled.
Teach robots to grasp objects
Machines still have a very long way to go to match human proficiency even at basic sensorimotor skills like grasping. A human child is able to reliably grasp objects after one year, and takes around four years to acquire more sophisticated precision grasps. However, networked robots can instantaneously share their experience with one another, so Google dedicated 14 separate robots to the job of learning grasping in parallel, so they can acquire the necessary experience much faster. Incorporating continuous feedback from networked robots into the machine learning system reduces the failures rate for grasping objects by nearly half.
Automatically generate reports
Arria helps its customers automatically generate reports, using natural language processing technology to learn how to write reports by scanning texts and determining relationships between concepts.