Machine learning has been around since the 1970s, but low power processors and limited data forced the progress of machine learning to slow down in the 1980s. Now with big data enabling the use of business data of unlimited variety, volume and velocity, machine learning has had a rebirth as a power player in the world of software algorithms. DATAVERSITY brought this interesting information to us in their article, “Deep Learning and Machine Learning Differences: Recent Views in an Ongoing Debate.”
In what seems a like tandem move, Google’s acquisition of UK-based Deep Mind resurrected the struggling field of deep learning. With deep learning, smart algorithms can aid computers to learn from one layer of data and apply that learning to the next layer without programming intervention. While machine learning encompasses the entire field of learning algorithms, deep learning involves specific types of learning models where the human programmer is not required to train computers. Deep learning trains the machine to do what the human brain does naturally.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.
