MACHINE LEARNING
Machine Learning focuses on development of computer programs that can access data and use it to learn for themselves.
This technology is an application of Artificial Intelligence (AI) which makes a system automatically learn and improve from experience without being explicitly programmed.
Machine Learning is capable of analyzing massive data quantities. It generally delivers faster, more accurate results in order to identify profitable opportunities or dangerous risks.
Machine Learning, AI & Cognitive Technologies can be a very effective combination when processing large volumes of information.
Most Common Machine Learning Algorithms:
Supervised Learning
Occurs when an algorithm learns from example data and associated target responses that can consist of numeric values or string labels, such as classes or tags, in order to later predict the correct response when posed with new examples.
Unsupervised Learning
Occurs when an algorithm learns from plain examples without any associated response, leaving the algorithm to determine the data patterns on its own.
Reinforcement Learning
Using this algorithm, the machine is trained to make specific decisions. The machine is exposed to an environment where it trains itself continually using trial and error.
Machine learning is widely applicable for:
- Healthcare Industry
- Financial Service Industry
- The Retail Industry
- The Automotive Industry
- Government Agencies
- Transportation Industry
- Oil & Gas Industry