Machine Learning In a Nutshell
Machine learning is a buzzword these days, usually in connection with big data and artificial intelligence. But do you know exactly what it is? Machine Learning is a sub-set of artificial intelligence where computer algorithms are used to autonomously learn from data and information. Machine learning computers can change and improve their algorithms all by themselves.
It is all about enlisting computers in the task of sorting through the massive amounts of data that modern technology has allowed us to generate (a.k.a. “big data”). It focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data.
Importance of machine learning
Today, machine learning algorithms enables computers to communicate with humans, autonomously drive cars, write and publish sport match reports, and find terrorist suspects. This will impact most industries and the jobs within them, which is why every manager should have at least some grasp of what machine learning is and how it is evolving.
Now it is possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results even on a very large scale. And by building precise models, an organization has a better chance of identifying profitable opportunities – or avoiding unknown risks.
How IoT can benefit from machine learning
IoT devices are generating tons of data, and machine learning is being employed to analyze and peruse that data to help improve efficiency and customer service, and reduce costs and energy consumption. To create a good learning system you need:
- data preparation capabilities
- algorithms - basic and advanced
- automation and iterative process
- ensemble modeling
Energy and air quality with machine learning
Air quality and different types of energy consumption apply artificial intelligence, big data and cloud computing to map complex, nonlinear air pollution trends accurately and efficiently. The method employs deep machine learning and gives intelligent advice to users and managers on how to save energy and get a better air quality. Solutions can now be recommended automatically and thanks to this technology, equipments can be recognized from a single metering point (NILM Technology).
To get the most value from machine learning, you have to know how to pair the best algorithms with the right tools and processes. Although machine learning is one of the biggest trends in detecting anything and everything these days, a lot of research still has to be done to test the algorithms.
WeSmart strives to integrate these new technologies into its platform and offer its customers new services and solutions based on machine learning.