Machine Learning Applications

by www.big-data.tips · Published March 21, 2017 · Updated March 21, 2017

Machine learning applications can be found in a wide variety of application domains that take advantage of learning from big data. Applications in this area are given when the problem to be solved changed in time or even depends on particular situations or environments. The key to those applications is to create a general-purpose ‘learning system’ that can adapt to their circumstances instead of explicitly writing a different program for each special circumstances.

One application area can be network when routing packets over a computer network with different usage peaks. There is a path maximizing the quality of service from a network source to a network destination, but it changes continuously as the network traffic usage changes. In this case a learning routing system would be able to adapt to the best path by taking into account the current network traffic. It learns from current network usage data. Another application is an intelligent user interface that can adapt to the biometrics of its user including accent, handwriting, working habits, productive hours, interactions with other users, and many other data learned from past experience in the system.

Other machine learning applications are already in practice in commercial domains. One very modern application area is recognizing speech and handwriting. Another application area often used by retail companies is to analyze past sales data in order to learn their customers behavior. This in turn enables the retail companies to improve on customer relationship management. Especially in financial organizations there are many application areas. One key application area in finance is to analyze past transactions to predict customers credit risks. Another highly studied application area is robotics. Modern robots use machine learning in order to optimize their behavior to complete a task using minimum resources..

Future machine learning applications that start to emerge in science, engineering and industry are also highly interesting for users and consumers. Cars starting to drive themselves under different road and weather conditions. Phones have started to translate speech to text, but in the future they might translate to and from a foreign language while speaking with another person over the phone in real-time. There will be in future also an increasing usage of robotics. Autonomous robots learn already to navigate in a new environment like a green grass field in order to cut the grass.