The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
Machine Learning can boost your analytics efforts by helping computer systems learn in a manner that simulates human learning. However, the technology you use to implement ML is not nearly as important as the thought process behind your implementation.
Many people I talk to---especially those in the C-suite---are excited about artificial intelligence (AI), and machine learning (ML). However, they're a little fuzzy on exactly how it can help them.
Automation is one of the most catalytic technologies in today's enterprise business. As a result, our workflows, analysis, and decision processes have accelerated to new heights over the past decade.
Discussing three broad categories of ML algorithms: supervised learning, unsupervised learning and hybrid
There are a few steps you can take to ensure that your ML initiative gets off, and stays, on the right footing.
Technological change is happening at a rapid pace, no more so than in Information Technology (IT).